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"morie_crypto_hkdf_sha256", "morie_crypto_hybrid_decrypt", "morie_crypto_hybrid_encrypt", "morie_crypto_hybrid_keygen", "morie_crypto_keystore_create", "morie_crypto_keystore_list", "morie_crypto_keystore_load", "morie_crypto_keystore_store", "morie_crypto_liboqs_available", "morie_crypto_liboqs_version", "morie_crypto_mldsa65_keygen", "morie_crypto_mldsa65_sign", "morie_crypto_mldsa65_verify", "morie_crypto_mlkem768_decaps", "morie_crypto_mlkem768_encaps", "morie_crypto_mlkem768_keygen", "morie_crypto_random_bytes", "morie_crypto_sodium_available", "morie_crypto_sodium_version", "morie_cutting_plane_sphere", "morie_dataset_catalog", "morie_dataset_column_profile", "morie_dataset_detect_role", "morie_dataset_infer_level", "morie_dataset_info", "morie_dataset_load", "morie_dataset_portal_catalog", "morie_dataset_portal_catalog_clear_cache", "morie_dataset_profile", "morie_dataset_profile_summary_table", "morie_dataset_profile_to_list", "morie_dataset_suggest_plan", "morie_dataset_summarize_column", "morie_datasets_arcgis_item_by_id", "morie_datasets_arcgis_item_metadata", "morie_datasets_arsau_aggregate_summary", "morie_datasets_arsau_detailed_dataset", "morie_datasets_arsau_uof_individual_records", "morie_datasets_arsau_uof_main_records", "morie_datasets_arsau_uof_probe_cycle_records", "morie_datasets_arsau_uof_weapon_records", "morie_datasets_bigquery", "morie_datasets_browse", "morie_datasets_calgary_community_crime_stats", "morie_datasets_calgary_fire_response_calls", "morie_datasets_calgary_fire_stations", "morie_datasets_calgary_open_crime_adjacent_layers", "morie_datasets_calgary_opendata_bulk_layers", "morie_datasets_calgary_socrata_by_id", "morie_datasets_chicago_arrests", "morie_datasets_chicago_community_areas", "morie_datasets_chicago_crime", "morie_datasets_chicago_crime_map", "morie_datasets_chicago_crime_odata", "morie_datasets_chicago_crime_resolved", "morie_datasets_chicago_crime_soql", "morie_datasets_chicago_iucr_codes", "morie_datasets_chicago_neighborhoods", "morie_datasets_chicago_opendata_bulk_layers", "morie_datasets_chicago_police_beats", "morie_datasets_chicago_police_districts", "morie_datasets_chicago_socrata_by_id", "morie_datasets_chicago_wards", "morie_datasets_ckan_package", "morie_datasets_ckan_search", "morie_datasets_corrections_uof_ethnic_origin", "morie_datasets_corrections_uof_incident_type", "morie_datasets_corrections_uof_incidents", "morie_datasets_corrections_uof_indigenous", "morie_datasets_corrections_uof_inmate_incident", "morie_datasets_corrections_uof_inmate_participant", "morie_datasets_corrections_uof_institution_summary", "morie_datasets_corrections_uof_location_summary", "morie_datasets_corrections_uof_race", "morie_datasets_corrections_uof_religion", "morie_datasets_corrections_uof_select_incident_summary", "morie_datasets_corrections_uof_staff_incident", "morie_datasets_cpads", "morie_datasets_cpd_public_arrests", "morie_datasets_edmonton_fire_stations", "morie_datasets_edmonton_open_crime_adjacent_layers", "morie_datasets_edmonton_opendata_bulk_layers", "morie_datasets_edmonton_police_stations", "morie_datasets_edmonton_socrata_by_id", "morie_datasets_external_socrata_layers", "morie_datasets_load_by_key", "morie_datasets_montreal_ckan_resource", "morie_datasets_montreal_justice_safety_layers", "morie_datasets_montreal_opendata_bulk_layers", "morie_datasets_montreal_sim_intervention_types", "morie_datasets_montreal_sim_interventions", "morie_datasets_namus_missing_persons", "morie_datasets_nibrs", "morie_datasets_nist_rds", "morie_datasets_nyc_boroughs", "morie_datasets_nyc_boundaries_catalog", "morie_datasets_nyc_community_districts", "morie_datasets_nyc_council_districts", "morie_datasets_nyc_ntas_2020", "morie_datasets_nyc_nypd_arrests_historic", "morie_datasets_nyc_nypd_arrests_ytd", "morie_datasets_nyc_nypd_boro_crosswalk", "morie_datasets_nyc_nypd_by_key", "morie_datasets_nyc_nypd_complaint_historic", "morie_datasets_nyc_nypd_complaint_ytd", "morie_datasets_nyc_nypd_hate_crimes", "morie_datasets_nyc_nypd_law_books", "morie_datasets_nyc_nypd_layers", "morie_datasets_nyc_nypd_offense_codes", "morie_datasets_nyc_nypd_resolved", "morie_datasets_nyc_nypd_uof_incidents", "morie_datasets_nyc_nypd_uof_subjects", "morie_datasets_nyc_nypd_vehicle_stops", "morie_datasets_nyc_opendata_bulk_layers", "morie_datasets_nyc_police_precincts", "morie_datasets_nyc_school_districts", "morie_datasets_nyc_socrata_by_id", "morie_datasets_nyc_stop_and_frisk", "morie_datasets_nyc_zctas", "morie_datasets_ontario_ckan_by_key", "morie_datasets_ontario_ckan_layers", "morie_datasets_otis_a01", "morie_datasets_otis_a01_restrictive_confinement", "morie_datasets_otis_b01_segregation_detailed", "morie_datasets_otis_b02_segregation_total_days", "morie_datasets_otis_b03_seg_alerts_by_institution", "morie_datasets_otis_b04_seg_consecutive_by_region", "morie_datasets_otis_b05_seg_consecutive_lengths", "morie_datasets_otis_b06_seg_reason_by_institution", "morie_datasets_otis_b07_seg_alerts_by_gender", "morie_datasets_otis_b08_seg_consecutive_by_institution", "morie_datasets_otis_b09_seg_n_times", "morie_datasets_otis_c01_individuals_total", "morie_datasets_otis_c02_individuals_by_institution", "morie_datasets_otis_c03_individuals_race_by_gender", "morie_datasets_otis_c04_individuals_race_by_region", "morie_datasets_otis_c05_individuals_religion_by_region", "morie_datasets_otis_c06_individuals_age_by_region", "morie_datasets_otis_c07_individuals_alerts", "morie_datasets_otis_c08_individuals_religion_by_gender", "morie_datasets_otis_c09_individuals_age_by_gender", "morie_datasets_otis_c10_aggregate_durations_by_institution", "morie_datasets_otis_c11_aggregate_lengths", "morie_datasets_otis_c12_aggregate_durations_by_region", "morie_datasets_otis_d01_deaths_in_custody", "morie_datasets_otis_d02_deaths_by_gender", "morie_datasets_otis_d03_deaths_by_race", "morie_datasets_otis_d04_deaths_by_religion", "morie_datasets_otis_d05_deaths_by_age_category", "morie_datasets_otis_d06_cause_by_alert", "morie_datasets_otis_d07_alerts_by_housing_unit", "morie_datasets_ottawa_open_crime_adjacent_layers", "morie_datasets_ottawa_opendata_bulk_layers", "morie_datasets_siu_director_reports", "morie_datasets_siu_report_fields", "morie_datasets_siu_report_text", "morie_datasets_statcan_ccjs_cubes", "morie_datasets_statcan_cube_metadata", "morie_datasets_statcan_full_csv_url", "morie_datasets_statcan_vectors", "morie_datasets_summary", "morie_datasets_toronto_ambulance_stations", "morie_datasets_toronto_asr_miscellaneous", "morie_datasets_toronto_open_ckan_resource", "morie_datasets_toronto_open_crime_adjacent_layers", "morie_datasets_toronto_opendata_bulk_layers", "morie_datasets_toronto_zoning_per_neighbourhood", "morie_datasets_tps_2008_firs", "morie_datasets_tps_2009_firs", "morie_datasets_tps_2010_firs", "morie_datasets_tps_2011_firs", "morie_datasets_tps_2012_firs", "morie_datasets_tps_2013_firs", "morie_datasets_tps_administrative", "morie_datasets_tps_arcgis_hub_by_id", "morie_datasets_tps_arcgis_hub_download", "morie_datasets_tps_arcgis_hub_layers", "morie_datasets_tps_arrested_and_charged_persons", "morie_datasets_tps_arrests_and_strip_searches", "morie_datasets_tps_assault", "morie_datasets_tps_automobile_ksi", "morie_datasets_tps_autotheft", "morie_datasets_tps_bicycle_thefts", "morie_datasets_tps_bicycletheft", "morie_datasets_tps_breakandenter", "morie_datasets_tps_budget_2020", "morie_datasets_tps_budget_2021", "morie_datasets_tps_budget_2022", "morie_datasets_tps_budget_2023", "morie_datasets_tps_budget_2024", "morie_datasets_tps_budget_2025", "morie_datasets_tps_budget_2026", "morie_datasets_tps_budget_by_command", "morie_datasets_tps_calls_for_service_attended", "morie_datasets_tps_community_safety_indicators", "morie_datasets_tps_complaint_dispositions", "morie_datasets_tps_cyclist_ksi", "morie_datasets_tps_dispatched_calls_by_division", "morie_datasets_tps_facilities", "morie_datasets_tps_fatals_ksi", "morie_datasets_tps_firearms_top_calibres", "morie_datasets_tps_gross_expenditures_by_division", "morie_datasets_tps_gross_operating_budget", "morie_datasets_tps_hatecrimes", "morie_datasets_tps_homicide", "morie_datasets_tps_homicides", "morie_datasets_tps_intimate_partner_family_violence", "morie_datasets_tps_investigated_alleged_misconduct", "morie_datasets_tps_killed_and_seriously_injured", "morie_datasets_tps_layers", "morie_datasets_tps_major_crime", "morie_datasets_tps_mha_apprehensions", "morie_datasets_tps_miscellaneous_calls_for_service", "morie_datasets_tps_miscellaneous_data", "morie_datasets_tps_miscellaneous_firearms", "morie_datasets_tps_motorcylist_ksi", "morie_datasets_tps_neighbourhood_crime_rates", "morie_datasets_tps_passenger_ksi", "morie_datasets_tps_patrol_zone", "morie_datasets_tps_pedestrian_ksi", "morie_datasets_tps_personnel_by_command", "morie_datasets_tps_personnel_by_rank", "morie_datasets_tps_personnel_by_rank_by_division", "morie_datasets_tps_persons_in_crisis_calls_for_service_attended", "morie_datasets_tps_police_divisions", "morie_datasets_tps_psdp_resolved", "morie_datasets_tps_regulated_interactions", "morie_datasets_tps_reported_crimes", "morie_datasets_tps_robbery", "morie_datasets_tps_search_of_persons", "morie_datasets_tps_shooting_firearm_discharges", "morie_datasets_tps_shootings", "morie_datasets_tps_staffing_by_command", "morie_datasets_tps_theft_from_motor_vehicle", "morie_datasets_tps_theft_over", "morie_datasets_tps_tickets_issued", "morie_datasets_tps_top_20_offences_of_firearm_seizures", "morie_datasets_tps_total_public_complaints", "morie_datasets_tps_traffic_collisions", "morie_datasets_tps_use_of_force_call_for_service_types", "morie_datasets_tps_use_of_force_call_sources_by_month", "morie_datasets_tps_use_of_force_gender_composition", "morie_datasets_tps_use_of_force_location_of_occurrences", "morie_datasets_tps_use_of_force_occurrence_category", "morie_datasets_tps_use_of_force_time_of_day_trends", "morie_datasets_tps_use_of_force_use_of_force_types_and_perceived_weapons", "morie_datasets_tps_victims_of_crime", "morie_datasets_vancouver_community_centres", "morie_datasets_vancouver_community_food_markets", "morie_datasets_vancouver_disability_parking", "morie_datasets_vancouver_fire_halls", "morie_datasets_vancouver_graffiti", "morie_datasets_vancouver_homeless_shelters", "morie_datasets_vancouver_noise_control_areas", "morie_datasets_vancouver_opendata_bulk_layers", "morie_datasets_vancouver_opendata_by_id", "morie_datasets_vancouver_opendata_layers", "morie_datasets_vancouver_property_use_inspection_districts", "morie_datasets_vancouver_public_art", "morie_datasets_vpd_crime", "morie_datasets_vpd_legal_disclaimer", "morie_db_connect", "morie_db_create_indexes", "morie_dbscan_clustering", "morie_dcc_multivariate_garch", "morie_decision_tree_split", "morie_deep_learning_genomic", "morie_default_synthetic_name_map", "morie_default_workflow_map", "morie_desc_atkinson", "morie_desc_cramers_v", "morie_desc_gini", "morie_desc_kappa", "morie_desc_winsorize", "morie_describe", "morie_describe_by_name", "morie_design_effect", "morie_det_rng", "morie_det_rng_sha_hex", "morie_did_2x2", "morie_did_aggregate_gt_att", "morie_did_bacon_decomposition", "morie_did_chaisemartin_dhaultfoeuille", "morie_did_continuous_treatment", "morie_did_diagnostics", "morie_did_doubly_robust", "morie_did_event_study", "morie_did_fuzzy", "morie_did_group_time_att", "morie_did_heterogeneous", "morie_did_panel_fe", "morie_did_parallel_trends_data", "morie_did_placebo_test_group", "morie_did_placebo_test_outcome", "morie_did_placebo_test_time", "morie_did_repeated_cross_section", "morie_did_sensitivity_analysis", "morie_did_staggered", "morie_did_synthdid_estimate", "morie_did_synthetic", "morie_did_test_parallel_trends", "morie_did_triple_difference", "morie_did_twoway_fe_weights", "morie_did_wild_cluster_bootstrap", "morie_diffu_diffusion_forward", "morie_diffu_heat_diffusion", "morie_diffusion_forward", "morie_dimensionality_test", "morie_download_bootstrap", "morie_dp_gaussian_mixture", "morie_dropout_forward", "morie_drpfw_dropout_forward", "morie_dsp_acf_from_psd", "morie_dsp_alpha_trimmed_mean", "morie_dsp_amplitude_histogram", "morie_dsp_arc_length", "morie_dsp_band_power", "morie_dsp_baseline_correlation", "morie_dsp_centroidal_time", "morie_dsp_coherence", "morie_dsp_coherence_spectrum", "morie_dsp_comb", "morie_dsp_complex_cepstrum", "morie_dsp_complex_demodulation", "morie_dsp_crest_factor", "morie_dsp_cross_correlation", "morie_dsp_csd", "morie_dsp_cv", "morie_dsp_derivative_detect", "morie_dsp_dicrotic_notch", "morie_dsp_ensemble_average", "morie_dsp_entropy_histogram", "morie_dsp_even_odd", "morie_dsp_fbm_synthesis", "morie_dsp_form_factor", "morie_dsp_fractal_dim_psd", "morie_dsp_hann_filter", "morie_dsp_higuchi_fd", "morie_dsp_hilbert_envelope", "morie_dsp_hjorth", "morie_dsp_hjorth_activity", "morie_dsp_hjorth_complexity", "morie_dsp_hjorth_mobility", "morie_dsp_homomorphic", "morie_dsp_hr_from_rr", "morie_dsp_integrated_emg", "morie_dsp_katz_fd", "morie_dsp_lms", "morie_dsp_matched", "morie_dsp_mean_abs", "morie_dsp_mean_frequency", "morie_dsp_median_filter", "morie_dsp_median_frequency", "morie_dsp_min_phase", "morie_dsp_moving_average", "morie_dsp_myopulse_rate", "morie_dsp_nlms", "morie_dsp_notch", "morie_dsp_onset_detect", "morie_dsp_pan_tompkins", "morie_dsp_parzen_pdf", "morie_dsp_psd_bartlett", "morie_dsp_psd_periodogram", "morie_dsp_psd_to_db", "morie_dsp_psd_welch", "morie_dsp_qrs_features", "morie_dsp_rls", "morie_dsp_rms", "morie_dsp_ruler_fd", "morie_dsp_shannon_energy", "morie_dsp_shape_factor", "morie_dsp_slope_sign_changes", "morie_dsp_snr", "morie_dsp_snr_improvement", "morie_dsp_spectral_edge", "morie_dsp_spectral_entropy", "morie_dsp_spectral_flatness", "morie_dsp_spectral_kurtosis", "morie_dsp_spectral_moment", "morie_dsp_spectral_ratio", "morie_dsp_synchronized_average", "morie_dsp_t_wave", "morie_dsp_teager_energy", "morie_dsp_template_match", "morie_dsp_threshold_detect", "morie_dsp_turning_points", "morie_dsp_turns_count", "morie_dsp_variance_ratio", "morie_dsp_waveform_length", "morie_dsp_waveform_length_norm", "morie_dsp_wiener_filter", "morie_dsp_wiener_hopf", "morie_dsp_willison_amplitude", "morie_dsp_window", "morie_dsp_zero_crossing", "morie_dynamic_wnominate", "morie_e_value", "morie_effects_comparisons", "morie_effects_emmeans", "morie_effects_predictions", "morie_effects_slopes", "morie_effects_tidy", "morie_eg_coint", "morie_egarch_model", "morie_ensure_extras", "morie_entheo_analyze_subject", "morie_entheo_available_subjects", "morie_entheo_clone_dmt_imaging", "morie_entheo_dataset_overview", "morie_entheo_dynamic_functional_connectivity", "morie_entheo_load_eeg_region", "morie_entheo_load_fmri_subject", "morie_entheo_lz_complexity", "morie_entheo_spectral_band_power", "morie_estimate_aipw", "morie_estimate_atc", "morie_estimate_ate", "morie_estimate_att", "morie_estimate_cate", "morie_estimate_double_ml", "morie_estimate_g_computation", "morie_estimate_gate", "morie_estimate_irm", "morie_estimate_late", "morie_estimate_propensity_scores", "morie_ewma_volatility", "morie_extreme_value_gev", "morie_fairness_apply_profile", "morie_fairness_average_odds_difference", "morie_fairness_bias_amplification", "MORIE_FAIRNESS_CANONICAL_FIELDS", "morie_fairness_city_profile", "morie_fairness_column_map", "morie_fairness_demographic_parity", "morie_fairness_disparate_impact", "morie_fairness_equalized_odds", "morie_fairness_get_city", "morie_fairness_gini", "morie_fairness_list_cities", "morie_fairness_noisy_or_detection", "morie_fairness_predpol_aggregate_areas", "morie_fairness_predpol_calibration_audit", "morie_fairness_predpol_score_disparity", "morie_fairness_predpol_temporal_audit", "morie_fairness_register_city", "morie_fairness_simulate_biased_crime_data", "morie_fairness_xai_ale", "morie_fairness_xai_ceteris_paribus", "morie_fairness_xai_partial_dependence", "morie_fairness_xai_permutation_importance", "morie_fairness_xai_shap_values", "morie_fast_available", "morie_fauzi_bias_reduced_kdfe", "morie_fauzi_cvm_smoothed", "morie_fauzi_edgeworth_quantile", "morie_fauzi_h_decomposition", "morie_fauzi_higher_order_kernel", "morie_fauzi_kdfe_properties", "morie_fauzi_kernel_quantile_asymptotic", "morie_fauzi_ks_smoothed", "morie_fauzi_l_statistic", "morie_fauzi_mise_computation", "morie_fauzi_mrl_asymptotic", "morie_fauzi_mrl_boundary_free", "morie_fauzi_smoothed_sign", "morie_fauzi_smoothed_wilcoxon", "morie_fauzi_survival_kernel", "morie_fdr_qvalues", "morie_fetch", "morie_fetch_arcgis", "morie_fetch_ckan", "morie_fetch_siu", "morie_fetch_tps", "morie_fisher_exact_test", "morie_forward_pass_dense", "morie_fwpas_forward_pass_dense", "morie_gan_loss", "morie_ganls_gan_loss", "morie_garch_fit", "morie_gblup_full", "morie_generalized_pareto", "morie_generate_ar_coefficients", "morie_generate_synthetic_data", "morie_generate_var_coefficients", "morie_genomic_cross_validation", "morie_geographically_weighted_regression", "morie_geostat_krige", "morie_geostat_variogram", "morie_ghosal_adaptation", "morie_ghosal_bernstein_von_mises", "morie_ghosal_contraction_rate", "morie_ghosal_dirichlet_posterior", "morie_ghosal_dpmixture_density", "morie_ghosal_empirical_bayes", "morie_ghosal_gp_matern", "morie_ghosal_gp_squared_exponential", "morie_ghosal_hierarchical_bayes", "morie_ghosal_log_density", "morie_ghosal_moment_matching", "morie_ghosal_neutral_right", "morie_ghosal_np_classification", "morie_ghosal_np_regression", "morie_ghosal_np_testing", "morie_ghosal_posterior_consistency", "morie_ghosal_sieve_prior", "morie_ghosal_stick_breaking_trunc", "morie_ghosal_survival_beta_process", "morie_ghosal_wavelet_prior", "morie_gpl_compatible_licenses", "morie_gradient_boosting_ensemble", "morie_gradient_boosting_genomic", "morie_gradient_descent_vanilla", "morie_grid_search_cv", "morie_grm_vanraden", "morie_gru_cell", "morie_grucl_gru_cell", "morie_gxe_interaction_model", "morie_hawkes_fit", "morie_he_initialization", "morie_heinz_he_initialization", "morie_horowitz_average_derivative", "morie_horowitz_bandwidth_bootstrap", "morie_horowitz_binary_response", "morie_horowitz_censored_regression", "morie_horowitz_deconvolution", "morie_horowitz_duration_model", "morie_horowitz_index_model", "morie_horowitz_kernel_density", "morie_horowitz_kernel_regression", "morie_horowitz_local_ate", "morie_horowitz_local_linear", "morie_horowitz_mixture_model", "morie_horowitz_nonparametric_iv", "morie_horowitz_plr_bandwidth", "morie_horowitz_plr_estimator", "morie_horowitz_quantile_regression", "morie_horowitz_sample_selection", "morie_horowitz_smoothed_maximum_score", "morie_horowitz_treatment_effect", "morie_horowitz_wild_bootstrap", "morie_hurst_r", "morie_ideal_point_model", "morie_ideal_point_recovery", "morie_importance_sampling", "morie_indicator_kriging", "morie_infer_measurement_level", "morie_ingest_bigquery_build_sql", "morie_ingest_bigquery_query", "morie_ingest_bigquery_table", "morie_ingest_chicago_crime", "morie_ingest_chicago_crime_bigquery", "morie_ingest_chicago_resources", "morie_ingest_chicago_socrata", "morie_ingest_cihi_xlsx", "morie_ingest_ckan_fetch_package_csvs", "morie_ingest_ckan_package_search", "morie_ingest_ckan_package_show", "morie_ingest_ckan_read_resource", "morie_ingest_ckan_resource_show", "morie_ingest_ckan_search_packages", "morie_ingest_forensics_namus_missing", "morie_ingest_forensics_nibrs", "morie_ingest_forensics_nist_rds", "morie_ingest_statcan_cansim", "morie_ingest_statcan_csv", "morie_ingest_tps_feature_layer", "morie_ingest_tps_fetch", "morie_ingest_tps_layers", "morie_inspect_output", "morie_install_extras", "morie_irt_spatial", "morie_is_over_legal_limit", "morie_isotonic_regression", "morie_iv_anderson_rubin", "morie_iv_anderson_rubin_ci", "morie_iv_conditional_lr", "morie_iv_control_function", "morie_iv_cragg_donald", "morie_iv_cue_gmm", "morie_iv_diagnostics", "morie_iv_durbin_wu_hausman", "morie_iv_first_stage_diagnostics", "morie_iv_gmm", "morie_iv_hansen_j", "morie_iv_hausman", "morie_iv_jive", "morie_iv_kleibergen_paap", "morie_iv_liml", "morie_iv_panel", "morie_iv_probit", "morie_iv_residual_analysis", "morie_iv_sargan", "morie_iv_split_sample", "morie_iv_stock_yogo", "morie_iv_tsls", "morie_iv_wald", "morie_jackknife_estimate", "morie_jackknife_estimator", "morie_johansen_cointegration", "morie_kalman_filter", "morie_kendall_tau", "morie_kendall_tau_partial", "morie_kernel_pca", "morie_kmeans_clustering", "morie_kosorok_bootstrap_empirical", "morie_kosorok_bracketing_number", "morie_kosorok_censoring_survival", "morie_kosorok_counting_process", "morie_kosorok_cox_partial_likelihood", "morie_kosorok_donsker_class", "morie_kosorok_efficient_score", "morie_kosorok_empirical_process", "morie_kosorok_glivenko_cantelli", "morie_kosorok_influence_function", "morie_kosorok_information_bound", "morie_kosorok_m_estimator", "morie_kosorok_maximal_inequality", "morie_kosorok_multiplier_bootstrap", "morie_kosorok_nelson_aalen", "morie_kosorok_one_step_estimator", "morie_kosorok_profile_likelihood", "morie_kosorok_tangent_space", "morie_kosorok_vc_dimension", "morie_kosorok_z_estimator", "morie_kruskal_wallis_test", "morie_ksr01_kosorok_empirical_process", "morie_ksr02_kosorok_donsker_class", "morie_ksr03_kosorok_glivenko_cantelli", "morie_ksr04_kosorok_vc_dimension", "morie_ksr05_kosorok_bracketing_number", "morie_ksr06_kosorok_maximal_inequality", "morie_ksr07_kosorok_bootstrap_empirical", "morie_ksr08_kosorok_multiplier_bootstrap", "morie_ksr09_kosorok_z_estimator", "morie_ksr10_kosorok_m_estimator", "morie_ksr11_kosorok_efficient_score", "morie_ksr12_kosorok_information_bound", "morie_ksr13_kosorok_tangent_space", "morie_ksr14_kosorok_profile_likelihood", "morie_ksr15_kosorok_one_step_estimator", "morie_ksr16_kosorok_influence_function", "morie_ksr17_kosorok_counting_process", "morie_ksr18_kosorok_nelson_aalen", "morie_ksr19_kosorok_cox_partial_likelihood", "morie_ksr20_kosorok_censoring_survival", "morie_laniyonu_actuarial_risk_disparity", "morie_laniyonu_gentrification_policing", "morie_laniyonu_smi_force_disparity", "morie_latin_hypercube", "morie_lcmm_latent_class", "morie_learning_curve", "morie_levene_test", "morie_license_metadata", "morie_linear_regression_ols", "morie_list_datasets", "morie_list_morie_modules", "morie_llm_agent_available", "morie_llm_ask", "morie_llm_ask_multi", "morie_llm_detect_provider", "morie_llm_list_freeapi_models", "morie_llm_probe_freeapi", "morie_llm_probe_ollama", "morie_llm_request_completion", "morie_load_cpads", "morie_load_cpads_data", "morie_load_dataset", "morie_locfdr_estimate", "morie_lstm_cell", "morie_lstmc_lstm_cell", "morie_mann_whitney_test", "morie_marker_variance", "morie_matching_abadie_imbens_se", "morie_matching_atc_matched", "morie_matching_ate_matched", "morie_matching_att_matched", "morie_matching_balance", "morie_matching_balance_table", "morie_matching_cardinality", "morie_matching_cem", "morie_matching_common_support", "morie_matching_doubly_robust", "morie_matching_entropy_balance", "morie_matching_estimate_propensity", "morie_matching_exact", "morie_matching_full", "morie_matching_genetic", "morie_matching_longitudinal", "morie_matching_love_plot_data", "morie_matching_mahalanobis", "morie_matching_multi_treatment", "morie_matching_nearest_neighbor", "morie_matching_optimal_pair", "morie_matching_overlap", "morie_matching_quality", "morie_matching_rosenbaum_bounds", "morie_matching_subclassify", "morie_matching_trim_propensity", "morie_matching_variable_ratio", "morie_maxpool_forward", "morie_mds_spatial_map", "morie_median_voter", "morie_meta_rma", "morie_mhatf_multi_head_attention_full", "morie_midas_regression", "morie_mini_batch_gradient", "morie_ml_apply_smote", "morie_ml_eval_robustness", "morie_monte_carlo_integration", "morie_multi_head_attention_full", "morie_multi_trait_gblup", "morie_multinomial_probit_spatial", "morie_mvn_with_covariance", "morie_mvnorm_pmv", "morie_mvnorm_sample", "morie_mxpol_maxpool_forward", "morie_nbeats_basis", "morie_nonstationary_covariance", "morie_np_kernel_reg", "morie_odds_ratio_ci", "morie_omega_squared", "morie_one_sample_coverage", "morie_one_sample_t_test", "morie_optimal_classification", "morie_ordered_alternatives_test", "morie_ordered_categories", "morie_ordinary_kriging", "morie_otis_aipw_ate", "morie_otis_aipw_superlearner", "morie_otis_alert_state_combo", "morie_otis_all_analyses", "morie_otis_analyze_a01", "morie_otis_analyze_a01_dlrm", "morie_otis_analyze_a01_mrm", "morie_otis_analyze_a01_mrm_alt_age", "morie_otis_analyze_a01_mrm_alt_gender", "morie_otis_analyze_a01_mrm_alt_toronto", "morie_otis_analyze_a01_mrm_per_year", "morie_otis_analyze_a01_mrm_subgroup_female", "morie_otis_analyze_a01_mrm_subgroup_male", "morie_otis_analyze_a01_ruhela_alt_age", "morie_otis_analyze_a01_ruhela_alt_gender", "morie_otis_analyze_a01_ruhela_alt_toronto", "morie_otis_analyze_a01_ruhela_formulations", "morie_otis_analyze_a01_ruhela_per_year", "morie_otis_analyze_a01_ruhela_subgroup_female", "morie_otis_analyze_a01_ruhela_subgroup_male", "morie_otis_analyze_a01_with_csi_context", "morie_otis_analyze_all", "morie_otis_analyze_b01", "morie_otis_analyze_b01_dlrm", "morie_otis_analyze_b01_mrm", "morie_otis_analyze_b01_mrm_alt_age", "morie_otis_analyze_b01_mrm_alt_gender", "morie_otis_analyze_b01_mrm_alt_toronto", "morie_otis_analyze_b01_mrm_per_year", "morie_otis_analyze_b01_mrm_subgroup_female", "morie_otis_analyze_b01_mrm_subgroup_male", "morie_otis_analyze_b01_ruhela_alt_age", "morie_otis_analyze_b01_ruhela_alt_gender", "morie_otis_analyze_b01_ruhela_alt_toronto", "morie_otis_analyze_b01_ruhela_formulations", "morie_otis_analyze_b01_ruhela_per_year", "morie_otis_analyze_b01_ruhela_subgroup_female", "morie_otis_analyze_b01_ruhela_subgroup_male", "morie_otis_analyze_b02", "morie_otis_analyze_b02_dlrm", "morie_otis_analyze_b02_mrm", "morie_otis_analyze_b02_mrm_alt_age", "morie_otis_analyze_b02_mrm_alt_region", "morie_otis_analyze_b02_ruhela_alt_age", "morie_otis_analyze_b02_ruhela_alt_region", "morie_otis_analyze_b02_ruhela_formulations", "morie_otis_analyze_b03", "morie_otis_analyze_b03_mrm_aggregate", "morie_otis_analyze_b03_ruhela_aggregate", "morie_otis_analyze_b04", "morie_otis_analyze_b04_mrm_aggregate", "morie_otis_analyze_b04_ruhela_aggregate", "morie_otis_analyze_b05", "morie_otis_analyze_b05_mandela_classification", "morie_otis_analyze_b05_ruhela_aggregate", "morie_otis_analyze_b06", "morie_otis_analyze_b06_mrm_aggregate", "morie_otis_analyze_b06_ruhela_aggregate", "morie_otis_analyze_b07", "morie_otis_analyze_b07_mrm_aggregate", "morie_otis_analyze_b07_ruhela_aggregate", "morie_otis_analyze_b08", "morie_otis_analyze_b08_mrm_aggregate", "morie_otis_analyze_b08_ruhela_aggregate", "morie_otis_analyze_b09", "morie_otis_analyze_b09_mrm_aggregate", "morie_otis_analyze_b09_ruhela_aggregate", "morie_otis_analyze_c_chi2", "morie_otis_analyze_c01", "morie_otis_analyze_c01_mrm_aggregate", "morie_otis_analyze_c01_mrm_aggregate_region_cluster", "morie_otis_analyze_c01_ruhela_aggregate", "morie_otis_analyze_c01_ruhela_aggregate_region_cluster", "morie_otis_analyze_c02", "morie_otis_analyze_c02_mrm_aggregate", "morie_otis_analyze_c02_ruhela_aggregate", "morie_otis_analyze_c03", "morie_otis_analyze_c03_mrm_aggregate", "morie_otis_analyze_c03_ruhela_aggregate", "morie_otis_analyze_c04", "morie_otis_analyze_c04_mrm_aggregate", "morie_otis_analyze_c04_mrm_aggregate_region_cluster", "morie_otis_analyze_c04_ruhela_aggregate", "morie_otis_analyze_c04_ruhela_aggregate_region_cluster", "morie_otis_analyze_c05", "morie_otis_analyze_c05_mrm_aggregate", "morie_otis_analyze_c05_ruhela_aggregate", "morie_otis_analyze_c06", "morie_otis_analyze_c06_mrm_aggregate", "morie_otis_analyze_c06_ruhela_aggregate", "morie_otis_analyze_c07", "morie_otis_analyze_c07_mrm_aggregate", "morie_otis_analyze_c07_ruhela_aggregate", "morie_otis_analyze_c08", "morie_otis_analyze_c08_mrm_aggregate", "morie_otis_analyze_c08_ruhela_aggregate", "morie_otis_analyze_c09", "morie_otis_analyze_c09_mrm_aggregate", "morie_otis_analyze_c09_ruhela_aggregate", "morie_otis_analyze_c10", "morie_otis_analyze_c10_mrm_aggregate", "morie_otis_analyze_c10_ruhela_aggregate", "morie_otis_analyze_c11", "morie_otis_analyze_c11_mandela_classification", "morie_otis_analyze_c11_mrm_aggregate", "morie_otis_analyze_c11_ruhela_aggregate", "morie_otis_analyze_c12", "morie_otis_analyze_c12_mrm_aggregate", "morie_otis_analyze_c12_ruhela_aggregate", "morie_otis_analyze_d_chi2", "morie_otis_analyze_d01", "morie_otis_analyze_d02", "morie_otis_analyze_d02_mrm_aggregate", "morie_otis_analyze_d02_ruhela_aggregate", "morie_otis_analyze_d03", "morie_otis_analyze_d03_mrm_aggregate", "morie_otis_analyze_d03_ruhela_aggregate", "morie_otis_analyze_d04", "morie_otis_analyze_d04_mrm_aggregate", "morie_otis_analyze_d04_ruhela_aggregate", "morie_otis_analyze_d05", "morie_otis_analyze_d05_mrm_aggregate", "morie_otis_analyze_d05_ruhela_aggregate", "morie_otis_analyze_d06", "morie_otis_analyze_d07", "morie_otis_analyze_otis_mandela_provincial_vs_federal", "morie_otis_analyze_ruhela_grid", "morie_otis_analyze_ruhela_master", "morie_otis_analyze_ruhela_per_year", "morie_otis_analyzers", "morie_otis_astcmb", "morie_otis_causal_grid", "morie_otis_churn_analyze_all", "morie_otis_classify_mandela_combo", "morie_otis_descriptives", "morie_otis_disciplinary_medical_overlap", "morie_otis_dml", "morie_otis_embedding_distribution", "morie_otis_intra_year_transition_matrix", "morie_otis_ipw_ate", "morie_otis_irm_dml", "morie_otis_irr_glmm_vm", "morie_otis_load", "morie_otis_make_pair_a", "morie_otis_make_pair_alert_to_volatility_a01", "morie_otis_make_pair_alert_to_volatility_all", "morie_otis_make_pair_alert_to_volatility_naive", "morie_otis_make_pair_alert_to_volatility_ruhela", "morie_otis_make_pair_b", "morie_otis_make_pair_c", "morie_otis_mortification_cooccurrence", "morie_otis_otdesc", "morie_otis_otdml", "morie_otis_path_complexity_gini", "morie_otis_plr", "morie_otis_psm", "morie_otis_psm_subclass", "morie_otis_rc_trends", "morie_otis_rctrnd", "morie_otis_regC_demog_contingency", "morie_otis_region_alert_state_richness", "morie_otis_regional_placement", "morie_otis_repeat_placement_concentration", "morie_otis_rplace", "morie_otis_tps_analyze_all", "morie_otis_tps_composite_overlay", "morie_otis_tps_per_region_rollup", "morie_otis_tps_yoy_correlation", "morie_otis_volat", "morie_otis_volatility", "morie_otis_within_year_placement_count", "morie_otis_within_year_region_diversity", "morie_paired_t_test", "morie_parse_nypd_law_code", "morie_party_alignment", "morie_paths", "morie_pca_dimension_reduction", "morie_pcg_filter", "morie_penalized_regression", "morie_penalized_spline", "morie_percentile_modified_rank", "morie_performance_check_collinearity", "morie_performance_check_model", "morie_performance_check_outliers", "morie_performance_r2", "morie_permutation_test_general", "morie_point_biserial_r", "morie_polarization_index", "morie_polynomial_regression", "morie_posab_positional_encoding_abs", "morie_positional_encoding_abs", "morie_power_prop_test", "morie_power_t_test", "morie_ppcor_partial", "morie_ppcor_semipartial", "morie_pps_sample", "morie_prediction_accuracy", "morie_predpol_aggregate_areas", "morie_predpol_calibration_audit", "morie_predpol_score_disparity", "morie_predpol_temporal_audit", "morie_profile_dataset", "morie_prophet_components", "morie_proportion_ci", "morie_psymet_alpha", "morie_psymet_alphadel", "morie_psymet_ave", "morie_psymet_bartlett", "morie_psymet_cr", "morie_psymet_discrimination", "morie_psymet_itemtotal", "morie_psymet_kmo", "morie_psymet_omega", "morie_psymet_parallel", "morie_psymet_splithalf", "morie_quantile_function", "morie_quantile_reg", "morie_random_forest_ensemble", "morie_random_forest_genomic", "morie_random_search_cv", "morie_randtests_bartels", "morie_randtests_runs", "morie_randtests_turning_point", "morie_rangayyan_adaptive_filter", "morie_rangayyan_approximate_entropy", "morie_rangayyan_ar_burg", "morie_rangayyan_coherence", "morie_rangayyan_correlation_dimension", "morie_rangayyan_dfa", "morie_rangayyan_eeg_bands", "morie_rangayyan_emg_rms", "morie_rangayyan_envelope", "morie_rangayyan_fir_filter", "morie_rangayyan_higuchi_fd", "morie_rangayyan_hrv", "morie_rangayyan_iir_filter", "morie_rangayyan_lyapunov", "morie_rangayyan_psd", "morie_rangayyan_qrs_detect", "morie_rangayyan_sample_entropy", "morie_rangayyan_stft", "morie_rangayyan_wavelet_denoise", "morie_rangayyan_zero_crossing", "morie_rank_based_test", "morie_rank_order_statistics", "morie_rank_placements", "morie_rdd_bandwidth_cct", "morie_rdd_bandwidth_ik", "morie_rdd_bandwidth_rot", "morie_rdd_bandwidth_sensitivity", "morie_rdd_bias_corrected", "morie_rdd_cattaneo_density", "morie_rdd_covariate_balance", "morie_rdd_density_test", "morie_rdd_discrete", "morie_rdd_donut", "morie_rdd_fuzzy", "morie_rdd_geographic", "morie_rdd_kernel_epanechnikov", "morie_rdd_kernel_gaussian", "morie_rdd_kernel_triangular", "morie_rdd_kernel_uniform", "morie_rdd_kink", "morie_rdd_local_polynomial", "morie_rdd_local_randinf", "morie_rdd_local_randomisation", "morie_rdd_mccrary", "morie_rdd_placebo_cutoff", "morie_rdd_plot_data", "morie_rdd_power", "morie_rdd_power_calc", "morie_rdd_sample_size", "morie_rdd_sharp", "morie_read_outputs_manifest", "morie_recommended_pair_test", "morie_recommended_summary", "morie_regime_switching", "morie_regularization_path", "morie_residual_connection", "morie_return_level", "morie_risk_difference_ci", "morie_risk_ratio_ci", "morie_rkhs_full", "morie_rkhs_kernel_regression", "morie_rnn_genomic", "morie_roc_auc_score", "morie_roll_call_analysis", "morie_rotary_position_embedding", "morie_rotrp_rotary_position_embedding", "morie_rsample_bootstraps", "morie_rslnk_residual_connection", "morie_run_ebac_selection_ipw_analysis", "morie_run_morie_module", "morie_run_morie_modules", "morie_run_pipeline", "morie_run_propensity_ipw_analysis", "morie_run_treatment_effects_analysis", "morie_run_weighted_logistic_analysis", "morie_run_workflow_step", "morie_sample", "morie_sample_size_logistic", "morie_scaled_dot_product_attention", "morie_sensitivity_evalue", "morie_sensitivity_konfound", "morie_sensitivity_omitted_var_bias", "morie_sensitivity_rosenbaum", "morie_sensitivity_tipping_point", "morie_sgolay_smooth", "morie_shapiro_wilk_test", "morie_sign_test_power", "morie_simple_random_sample", "morie_simpleboot_two", "morie_simulate_longitudinal_panel", "morie_siu_all_analyses", "morie_siu_anomaly_check", "morie_siu_audit_case", "morie_siu_audit_columns", "morie_siu_by_police_service", "morie_siu_by_year", "morie_siu_cache_path", "morie_siu_case_counts", "morie_siu_charges_by_year_chi2", "morie_siu_classify_mandela", "morie_siu_compare", "morie_siu_decision_timing", "morie_siu_demographics", "morie_siu_fetch_cases", "morie_siu_fetch_dataframe", "morie_siu_index", "morie_siu_index_url", "morie_siu_llm_extract", "morie_siu_mental_health_race_indicators", "morie_siu_parse_html", "morie_siu_parse_news_html", "morie_siu_record_correction", "morie_siu_refresh_manifest", "morie_siu_sanity_check", "morie_siu_sprott_doob_feb2021", "morie_siu_sprott_doob_iftene_table1", "morie_siu_sprott_doob_iftene_table10", "morie_siu_sprott_doob_iftene_table15", "morie_siu_sprott_doob_iftene_table9", "morie_siu_sprott_doob_table11", "morie_siu_sprott_doob_table12", "morie_siu_sprott_doob_table13", "morie_siu_sprott_doob_table15", "morie_siu_sprott_doob_table19", "morie_siu_sprott_doob_table22", "morie_siu_sprott_doob_table23", "morie_siu_sprott_doob_table4", "morie_siu_translate", "morie_siu_translate_fr_to_en", "morie_siu_verify_chi2", "morie_siu_verify_published_chi_squares", "MORIE_SIUIAP_AFFIDAVITS", "morie_siuiap_cite", "MORIE_SIUIAP_CRIMSL_REPORTS", "MORIE_SIUIAP_ORIGINAL_PANEL_2019_2020", "MORIE_SIUIAP_PANEL_MANDATE", "MORIE_SIUIAP_PANEL_MEMBERS", "morie_siuiap_panel_summary", "MORIE_SIUIAP_REPORTS", "MORIE_SIUIAP_URL", "morie_sobol_sequence", "morie_spatial_agreement", "morie_spatial_ar_error", "morie_spatial_ar_lag", "morie_spatial_autocorrelation", "morie_spatial_block_kriging", "morie_spatial_cross_validation", "morie_spatial_glm", "morie_spatial_mixed_model", "morie_spatial_trend_surface", "morie_spatial_voting_aldrich_mckelvey", "morie_spatial_voting_alpha_nominate", "morie_spatial_voting_anchoring_vignettes", "morie_spatial_voting_bayesian_am", "morie_spatial_voting_bayesian_irt_likelihood", "morie_spatial_voting_bayesian_irt_posterior", "morie_spatial_voting_bayesian_mds", "morie_spatial_voting_bayesian_unfolding", "morie_spatial_voting_blackbox", "morie_spatial_voting_cjr_irt", "morie_spatial_voting_classical_mds", "morie_spatial_voting_cutting_lines", "morie_spatial_voting_double_centering", "morie_spatial_voting_dw_nominate", "morie_spatial_voting_dynamic_irt", "morie_spatial_voting_em_irt", "morie_spatial_voting_ideal_point_recovery", "morie_spatial_voting_indscal", "morie_spatial_voting_mds_fit_stats", "morie_spatial_voting_mlsmu6", "morie_spatial_voting_nominate_bootstrap", "morie_spatial_voting_nominate_loglik", "morie_spatial_voting_nominate_utility", "morie_spatial_voting_nominate_vote_prob", "morie_spatial_voting_nonmetric_mds", "morie_spatial_voting_nonparametric_bootstrap", "morie_spatial_voting_normal_vectors", "morie_spatial_voting_optimal_classification", "morie_spatial_voting_ordered_oc", "morie_spatial_voting_ordinal_irt", "morie_spatial_voting_procrustes", "morie_spatial_voting_smacof", "morie_spatial_voting_smacof_unfolding", "morie_spatial_voting_unfolding_stress", "morie_spatial_voting_wordfish", "morie_spatiotemporal_autocovariance", "morie_spatiotemporal_kriging", "morie_spatiotemporal_variogram", "morie_spearman_rho", "morie_specs_from_df", "morie_spectral_cluster", "morie_spectral_density", "morie_state_space_model", "morie_stratified_sample", "morie_stratified_sampling", "morie_suggest_analysis_plan", "morie_sukhatme_test", "morie_summarize_output_audit", "morie_survey_calibrate", "morie_survey_complex_glm", "morie_survey_design", "morie_survey_glm", "morie_survey_hajek_mean", "morie_survey_ht_total", "morie_survey_mean", "morie_survey_poststratify", "morie_survey_ratio", "morie_survey_subpop", "morie_survival_aft", "morie_survival_cif", "morie_survival_compare_parametric", "morie_survival_concordance", "morie_survival_cox", "morie_survival_coxsnell", "morie_survival_deviance", "morie_survival_finegray", "morie_survival_hr", "morie_survival_km", "morie_survival_landmark", "morie_survival_left_truncated_km", "morie_survival_logrank", "morie_survival_martingale", "morie_survival_nelsonaalen", "morie_survival_parametric", "morie_survival_rmst", "morie_survival_rmst_diff", "morie_survival_schoenfeld", "morie_survival_turnbull", "morie_svm_genomic", "morie_svm_hinge_primal", "morie_svm_kernel_trick", "morie_sync_rng", "morie_synth_corrections_uof", "morie_synth_otis", "morie_synth_otis_all", "morie_terry_hoeffding_test", "morie_tgarch_model", "morie_thin_plate_spline", "morie_threshold_autoregression", "morie_to_hood_crosswalk", "morie_to_neighbourhoods", "morie_tolerance_limits", "morie_tps_add_hood_140_from_158", "morie_tps_add_hood_158_from_140", "morie_tps_aggregate_158_to_140", "morie_tps_analyze_all", "morie_tps_analyze_assault", "morie_tps_analyze_autotheft", "morie_tps_analyze_bicycletheft", "morie_tps_analyze_breakandenter", "morie_tps_analyze_communitysafetyindicators", "morie_tps_analyze_csi_from_dataframes", "morie_tps_analyze_hatecrimes", "morie_tps_analyze_homicides", "morie_tps_analyze_intimatepartnerandfamilyviolence", "morie_tps_analyze_neighbourhoodcrimerates", "morie_tps_analyze_one", "morie_tps_analyze_robbery", "morie_tps_analyze_shootingandfirearmdiscarges", "morie_tps_analyze_theftfrommovingvehicle", "morie_tps_analyze_theftover", "morie_tps_arima_forecast", "morie_tps_assert_hood_version", "morie_tps_available_formats", "morie_tps_bivariate_moran", "morie_tps_bivariate_morans_i", "morie_tps_category_correlation_matrix", "morie_tps_changepoint_detection", "morie_tps_compare_hawkes_kernels", "morie_tps_composite_index", "morie_tps_crime_compare", "morie_tps_criminal_network_graph", "MORIE_TPS_CSI_CATEGORIES", "morie_tps_csi_per_neighbourhood", "morie_tps_csi_per_year", "morie_tps_csi_weight", "morie_tps_data_dir", "morie_tps_dbscan_clusters", "morie_tps_disaggregate_140_to_158", "morie_tps_district_for_centroid", "morie_tps_fetch_category", "morie_tps_fetch_dataframe", "morie_tps_fokker_planck_grid", "morie_tps_getis_ord_g_star", "morie_tps_gini_concentration", "morie_tps_hawkes_advanced_fit", "morie_tps_hawkes_markovian_vs_nonmarkovian", "morie_tps_hawkes_temporal_fit", "morie_tps_inspection_game_phase", "morie_tps_kde_density", "morie_tps_langevin_simulate", "morie_tps_layer_urls", "MORIE_TPS_LAYER_URLS", "morie_tps_levy_flight_alpha", "morie_tps_list_categories", "morie_tps_list_datasets", "morie_tps_list_formats", "morie_tps_load", "morie_tps_load_dataset", "morie_tps_local_morans_i", "morie_tps_lotka_volterra_police_crime", "morie_tps_moran_sweep_heatmap", "morie_tps_morans_i_neighbourhood", "morie_tps_neighbourhood_concentration", "morie_tps_offence_summary", "morie_tps_polygon_morans_i", "morie_tps_pretty_label", "morie_tps_project_xy", "morie_tps_psdp_layers", "MORIE_TPS_REGISTRY", "morie_tps_render_choropleth", "morie_tps_render_dbscan", "morie_tps_render_district_proportional", "morie_tps_render_points", "morie_tps_render_quad", "morie_tps_render_satscan_panel", "morie_tps_render_yearly_grid", "morie_tps_resolve_hood_col", "morie_tps_ripley_k", "morie_tps_sarima_forecast", "morie_tps_sdb_reaction_diffusion", "morie_tps_sdb_turing_demo", "morie_tps_seasonal_pattern", "morie_tps_spatial_summary", "morie_tps_statphysics_analyze_all", "MORIE_TPS_SUPPORTED_FORMATS", "morie_tps_temporal_summary", "MORIE_TPS_TORONTO_POPULATION_BY_YEAR", "MORIE_TPS_TOTAL_CSI_WEIGHTS", "morie_tps_urban_scaling_beta", "morie_tps_use_of_force", "MORIE_TPS_VIOLENT_CSI_WEIGHTS", "morie_tps_year_over_year_trend", "morie_tps_year_to_hood_version", "morie_tps_yoy_panel", "morie_tpsuof", "morie_transformer_block", "morie_transformer_genomic", "morie_trfbl_transformer_block", "morie_tsne_reduction", "morie_two_sample_coverage", "morie_two_sample_t_test", "morie_unfolding_analysis", "morie_universal_kriging", "morie_unobserved_components", "morie_userguide", "morie_vae_elbo", "morie_vaenc_vae_elbo", "morie_validate_cpads_data", "morie_validate_outputs_manifest", "morie_van_der_waerden_test", "morie_variogram_estimation", "morie_variogram_fitting", "morie_vecm", "morie_verify_statistical_output", "morie_vertex_access_token", "morie_vertex_ask_gemini", "morie_vertex_health_check", "morie_vertex_resolve_config", "morie_vine_copula", "morie_voting_power_index", "morie_vpd_download_instructions", "morie_wavelet_time_series", "morie_weights_bootstrap", "morie_weights_brr", "morie_weights_calibrate_to_totals", "morie_weights_combined", "morie_weights_deff", "morie_weights_design", "morie_weights_detect_extreme", "morie_weights_diagnostics", "morie_weights_ess", "morie_weights_fay_brr", "morie_weights_greg", "morie_weights_jackknife", "morie_weights_multiframe", "morie_weights_nonresponse", "morie_weights_normalize", "morie_weights_poststratify", "morie_weights_propensity_nonresponse", "morie_weights_rake", "morie_weights_replicate_variance", "morie_weights_sdr", "morie_weights_smooth", "morie_weights_trim", "morie_wilcoxon_power", "morie_wilcoxon_signed_rank_test", "morie_wnominate", "morie_wnominate_estimate", "morie_write_audit_markdown", "morie_write_synthetic_data", "morie_xavier_initialization", "morie_xavir_xavier_init", "morie_xgboost_objective", "mrm_anova_bonferroni", "mrm_anova_oneway", "mrm_anova_power", "mrm_assumptions_check", "mrm_causal_design", "mrm_check_balancing", "mrm_check_overlap", "mrm_classify_mandela", "mrm_clt_demo", "mrm_factorial_2k", "mrm_fractional_factorial", "mrm_gentrification_panel", "mrm_graeco_latin", "mrm_latin_square", "mrm_mc_power", "mrm_median_causal_effect", "mrm_morans_i", "mrm_oneprop_test", "mrm_otis_mandela_spectrum", "mrm_otis_mortification_cooccurrence", "mrm_otis_placement_concentration", "mrm_otis_region_locality", "mrm_otis_seg_duration_km", "mrm_perm_block", "mrm_pit", "mrm_qq_plot", "mrm_random_latin", "mrm_rcbd", "mrm_response_surface", "mrm_siu_case_to_decision_km", "mrm_siu_outcome_classifier", "mrm_siu_per_service_rate", "mrm_spatial_spillover_decomposition", "mrm_standardised_difference", "mrm_synthetic_area_exposure", "mrm_threshold_coefficient", "mrm_threshold_specific_ordinal", "mrm_tps_kulldorff_scan", "mrm_tps_levy_scaling", "mrm_tps_lisa", "mrm_tps_load_hawkes_refit", "mrm_tps_moran_clustering", "mrm_tps_neighbourhood_recurrence_km", "mrm_tps_polygon_moran_per_year", "mrm_two_treatment_test", "mrm_twoprop_test", "mrm_uof_data_quality_audit", "mrm_uof_demographic_disparity", "mrm_uof_force_concentration", "mrm_uof_region_locality", "mrm_uof_weapon_diversity", "mrm_uof_yoy_change", "mrm_var_test", "n_effective_tests", "n_stat_commands", "nested_cross_validate", "normality_suite", "nstat", "number_needed_to_harm", "number_needed_to_treat", "nw_regression", "odds_ratio", "odds_ratio_table", "okrig", "omega_squared", "omitted_variable_bias", "one_proportion_ztest", "one_sample_ttest", "one_way_anova", "optcl", "or_to_d", "or_to_r", "paired_permutation_test", "paired_ttest", "parametric_bootstrap", "partial_correlation", "partial_eta_squared", "pburg", "pcgenv", "pcgmur", "pcgseg", "pearson_correlation", "permt", "permutation_fdr", "permutation_fwer", "permutation_test", "pettitt_changepoint", "pfd", "ph_assumption_test", "phi_coefficient", "point_biserial_correlation", "polrz", "prediction_interval", "probabilistic_bias_analysis", "pspln", "quntf", "r_effect_size", "r_squared", "r_to_d", "r_to_or", "ramsey_reset_test", "random_effects_meta", "rank_biserial_correlation", "rate_ratio", "rcall", "register_stat_command", "regression_table", "repeated_cv", "repeated_measures_anova", "resolve_stat_command", "retlv", "rgadp", "rgapn", "rgarb", "rgcoh", "rgcrl", "rgdfa", "rgeeg", "rgemg", "rgenv", "rgfir", "rghfd", "rghrv", "rgiir", "rglyp", "rgpsd", "rgqrs", "rgsam", "rgstf", "rgwav", "rgzcr", "risk_difference", "risk_ratio", "rkhsc", "rosenbaum_bounds", "rrint", "run_stat_command", "runs_test", "sampen", "sarla", "sarre", "score_data_quality", "score_test", "semi_partial_correlation", "SemiparKernels", "sensitivity_rosenbaum", "sensitivity_summary", "sglm", "sgolay", "sidak", "silverman_bandwidth", "simes_combined", "smixd", "sobls", "spblk", "spcrs", "spearman_correlation", "specification_curve", "sptag", "sptau", "sptrn", "stacv", "standardized_coefficients", "stat_bridge_exec", "stat_bridge_fn_info", "stat_bridge_fn_search", "stat_bridge_help", "stat_bridge_main", "stat_bridge_registry_json", "stat_bridge_verify", "stat_command", "stkrg", "storey_q", "stouffer_combined", "strat", "stvar", "subsampling", "summary_statistics_table", "table1", "temporal_validate", "tippett_combined", "tipping_point_analysis", "tpspn", "treatment_effect_table", "two_proportion_ztest", "two_sample_ttest", "two_way_anova", "ukrig", "unfdl", "validate_schema", "vargha_delaney_a", "variance_equality_suite", "variance_ratio", "vines", "vrgft", "vrgm", "vtpwr", "wald_test", "welch", "welch_ttest", "wilcoxon_signed_rank", "wild_bootstrap", "wnom" ], "_datasets": [ { "name": "ckan_metadata", "title": "CKAN Metadata for Open Data APIs", "object": "ckan_metadata", "class": [ "data.frame" ], "fields": [ "survey", "name", "package_id" ], "rows": 3, "table": true, "tojson": true }, { "name": "dataset_catalog", "title": "MORIE Dataset Catalog", "object": "dataset_catalog", "class": [ "data.frame" ], "fields": [ "key", "name", "source", "survey" ], "rows": 3, "table": true, "tojson": true }, { "name": "substance_categories", "title": "Substance Categories", "object": "substance_categories", "class": [ "data.frame" ], "fields": [ "key", "label" ], "rows": 11, "table": true, "tojson": true } ], "_help": [ { "page": "adjust_p_values", "title": "Convenience dispatcher for p-value adjustment methods", "topics": [ "adjust_p_values" ] }, { "page": "all_stat_command_names", "title": "Sorted vector of all command names + aliases", "topics": [ "all_stat_command_names" ] }, { "page": "analyze_doob_full_affidavit", "title": "Replicate Doob's full Federal Court affidavit (Tables 1-3)", "topics": [ "analyze_doob_full_affidavit" ] }, { "page": "analyze_doob_table1_releases", "title": "Analyse Doob Affidavit Table 1 — 5-year average annual releases", "topics": [ "analyze_doob_table1_releases" ] }, { "page": "analyze_doob_table2_flow", "title": "Analyse Doob Affidavit Table 2 — prisoner flow", "topics": [ "analyze_doob_table2_flow" ] }, { "page": "analyze_doob_table3_age_overrepresentation", "title": "Analyse Doob Affidavit Table 3 — age over-/under-representation", "topics": [ "analyze_doob_table3_age_overrepresentation" ] }, { "page": "anova_table", "title": "ANOVA table from a fitted model", "topics": [ "anova_table" ] }, { "page": "arsau", "title": "ARSAU dataset loaders + registry (R-side mirror of morie.arsau_datasets)", "topics": [ "arsau" ] }, { "page": "arsau_analyze", "title": "Per-record-type ARSAU analysis pipelines (R-side mirror of 'morie.arsau_analyze').", "topics": [ "arsau_analyze" ] }, { "page": "arsau_datasets", "title": "ARSAU CKAN sidecar helpers + tidy registry view (R-side companion to 'morie.arsau_datasets').", "topics": [ "arsau_datasets" ] }, { "page": "ARSAU_KINDS", "title": "Known ARSAU dataset kinds.", "topics": [ "ARSAU_KINDS" ] }, { "page": "ARSAU_REGISTRY", "title": "Return the ARSAU registry as a list of entries.", "topics": [ "ARSAU_REGISTRY" ] }, { "page": "ARSAU_YEARS", "title": "Known ARSAU year/range keys.", "topics": [ "ARSAU_YEARS" ] }, { "page": "assess_calibration", "title": "Comprehensive calibration assessment for binary outcomes", "topics": [ "assess_calibration" ] }, { "page": "assess_discrimination", "title": "Discrimination assessment for binary classifier", "topics": [ "assess_discrimination" ] }, { "page": "audit_variables", "title": "Comprehensive per-variable audit walker (R-side mirror)", "topics": [ "audit_variables" ] }, { "page": "auto_test", "title": "Automatic test selection", "topics": [ "auto_test" ] }, { "page": "bartlett_test", "title": "Bartlett's test for equality of variances", "topics": [ "bartlett_test" ] }, { "page": "benjamini_hochberg", "title": "Benjamini-Hochberg FDR control", "topics": [ "benjamini_hochberg", "bh" ] }, { "page": "benjamini_yekutieli", "title": "Benjamini-Yekutieli FDR control under arbitrary dependence", "topics": [ "benjamini_yekutieli", "by_fdr" ] }, { "page": "bias_adjusted_estimate", "title": "Bias-adjusted treatment effect (Ding & VanderWeele 2016)", "topics": [ "bias_adjusted_estimate" ] }, { "page": "block_bootstrap", "title": "Block bootstrap for dependent / time-series data", "topics": [ "block_bootstrap" ] }, { "page": "bonferroni", "title": "Bonferroni FWER correction", "topics": [ "bonferroni" ] }, { "page": "bootstrap", "title": "Nonparametric bootstrap inference", "topics": [ "bootstrap" ] }, { "page": "bootstrap_632", "title": ".632 and .632+ bootstrap estimators for prediction error", "topics": [ "bootstrap_632" ] }, { "page": "bootstrap_effect_size_ci", "title": "Generic bootstrap CI wrapper for any effect-size function", "topics": [ "bootstrap_effect_size_ci" ] }, { "page": "bootstrap_validate", "title": "Bootstrap .632 / .632+ validation", "topics": [ "bootstrap_validate" ] }, { "page": "buttbp", "title": "Butterworth bandpass filter", "topics": [ "buttbp" ] }, { "page": "buttbs", "title": "Butterworth bandstop (notch) filter", "topics": [ "buttbs" ] }, { "page": "butthp", "title": "Butterworth highpass filter", "topics": [ "butthp" ] }, { "page": "buttlp", "title": "Butterworth lowpass filter", "topics": [ "buttlp" ] }, { "page": "cauchy_combination", "title": "Cauchy combination test (Liu and Xie 2020)", "topics": [ "cauchy_combination" ] }, { "page": "CCRSO_TABLE1_RELEASES", "title": "CCRSO Table 1 — 5-year average annual conditional releases", "topics": [ "CCRSO_TABLE1_RELEASES" ] }, { "page": "CCRSO_TABLE2_FLOW", "title": "CCRSO Table 2 — prisoner flow 2013/14-2017/18", "topics": [ "CCRSO_TABLE2_FLOW" ] }, { "page": "CCRSO_TABLE3_AGE", "title": "CCRSO/StatsCan Table 3 — 2018 age distribution", "topics": [ "CCRSO_TABLE3_AGE" ] }, { "page": "cepst", "title": "Real cepstrum", "topics": [ "cepst" ] }, { "page": "cheatsheet", "title": "Print the morie cheat sheet", "topics": [ "cheatsheet" ] }, { "page": "check_referential_integrity", "title": "Check referential integrity (child FK -> parent PK)", "topics": [ "check_referential_integrity" ] }, { "page": "chi2_goodness_of_fit", "title": "Chi-squared goodness-of-fit test", "topics": [ "chi2_goodness_of_fit" ] }, { "page": "chi2_independence", "title": "Chi-squared test of independence", "topics": [ "chi2_independence" ] }, { "page": "ckan_metadata", "title": "CKAN Metadata for Open Data APIs", "topics": [ "ckan_metadata" ] }, { "page": "cles", "title": "Common Language Effect Size (probability of superiority)", "topics": [ "cles" ] }, { "page": "cliffs_delta", "title": "Cliff's delta", "topics": [ "cliffs_delta" ] }, { "page": "cochrans_q", "title": "Cochran's Q test", "topics": [ "cochrans_q" ] }, { "page": "coef.crr", "title": "S3 coef method for cmprsk::crr objects.", "topics": [ "coef.crr" ] }, { "page": "coefficient_of_variation", "title": "Coefficient of variation", "topics": [ "coefficient_of_variation" ] }, { "page": "cohens_f", "title": "Cohen's f from eta-squared", "topics": [ "cohens_f" ] }, { "page": "cohens_kappa", "title": "Cohen's kappa for two raters", "topics": [ "cohens_kappa" ] }, { "page": "cohens_w", "title": "Cohen's w for chi-squared", "topics": [ "cohens_w" ] }, { "page": "collinearity_diagnostics", "title": "Comprehensive multicollinearity diagnostics", "topics": [ "collinearity_diagnostics" ] }, { "page": "column_rule", "title": "Construct a column rule", "topics": [ "column_rule" ] }, { "page": "commands_by_category", "title": "Commands grouped by category", "topics": [ "commands_by_category" ] }, { "page": "compute_goodness_of_fit", "title": "Comprehensive goodness-of-fit statistics", "topics": [ "compute_goodness_of_fit" ] }, { "page": "compute_influence", "title": "Compute leverage and influence diagnostics", "topics": [ "compute_influence" ] }, { "page": "compute_residuals", "title": "Compute residual diagnostics", "topics": [ "compute_residuals" ] }, { "page": "compute_vif", "title": "Variance Inflation Factors", "topics": [ "compute_vif" ] }, { "page": "correlation_matrix", "title": "Pairwise correlation matrix with p-values", "topics": [ "correlation_matrix" ] }, { "page": "correlation_table", "title": "Pairwise correlation matrix with significance stars", "topics": [ "correlation_table" ] }, { "page": "create_reproducibility_manifest", "title": "Create a manifest of the environment for reproducibility", "topics": [ "create_reproducibility_manifest" ] }, { "page": "cross_validate", "title": "Cross-validate a model using a user-supplied fit/predict pair", "topics": [ "cross_validate" ] }, { "page": "d_to_nnt", "title": "Convert Cohen's d to NNT given a control event rate", "topics": [ "d_to_nnt" ] }, { "page": "d_to_or", "title": "Convert Cohen's d to odds ratio", "topics": [ "d_to_or" ] }, { "page": "d_to_r", "title": "Convert Cohen's d to Pearson r", "topics": [ "d_to_r" ] }, { "page": "dagostino_pearson", "title": "D'Agostino-Pearson omnibus normality test", "topics": [ "dagostino_pearson" ] }, { "page": "dataset_catalog", "title": "MORIE Dataset Catalog", "topics": [ "dataset_catalog" ] }, { "page": "decision_curve_analysis", "title": "Decision curve analysis", "topics": [ "decision_curve_analysis" ] }, { "page": "decoupling_test", "title": "Doob decoupling test", "topics": [ "decoupling_test" ] }, { "page": "delete_d_jackknife", "title": "Delete-d (generalised) jackknife", "topics": [ "delete_d_jackknife" ] }, { "page": "detect_overfitting", "title": "Bootstrap optimism-corrected performance", "topics": [ "detect_overfitting" ] }, { "page": "dfa", "title": "Detrended fluctuation analysis (DFA)", "topics": [ "dfa" ] }, { "page": "doob_trends", "title": "Doob Federal Court Affidavit — national-aggregate trend analyses", "topics": [ "doob_trends" ] }, { "page": "e_value", "title": "E-value for unmeasured confounding (continuous-ATE scale)", "topics": [ "e_value" ] }, { "page": "e_value_d", "title": "E-value for a standardised mean difference (Cohen's d)", "topics": [ "e_value_d" ] }, { "page": "e_value_hr", "title": "E-value for a hazard ratio", "topics": [ "e_value_hr" ] }, { "page": "e_value_or", "title": "E-value for an odds ratio", "topics": [ "e_value_or" ] }, { "page": "e_value_rr", "title": "E-value for a risk ratio", "topics": [ "e_value_rr" ] }, { "page": "ecgdet", "title": "Pan-Tompkins QRS / R-peak detector", "topics": [ "ecgdet" ] }, { "page": "effect_size_result", "title": "Build an effect-size result", "topics": [ "effect_size_result" ] }, { "page": "effect_sizes", "title": "Comprehensive effect-size calculations", "topics": [ "effect_sizes" ] }, { "page": "effects", "title": "Treatment effect estimators and marginal-effects extenders", "topics": [ "effects" ] }, { "page": "epsilon_squared", "title": "Epsilon-squared (Kelley, 1935)", "topics": [ "epsilon_squared" ] }, { "page": "estimate_ate", "title": "IPW-weighted OLS ATE", "topics": [ "estimate_ate" ] }, { "page": "estimate_ate_gcomputation", "title": "G-computation ATE with bootstrap SE", "topics": [ "estimate_ate_gcomputation" ] }, { "page": "estimate_pi0", "title": "Estimate the proportion of true null hypotheses (pi0)", "topics": [ "estimate_pi0" ] }, { "page": "estimate_pliv", "title": "Partially Linear IV (PLIV) / Local Average Treatment Effect", "topics": [ "estimate_pliv" ] }, { "page": "estimate_plr", "title": "Partially Linear Regression (PLR) ATE", "topics": [ "estimate_plr" ] }, { "page": "explain_file", "title": "Human-readable description of a morie output CSV", "topics": [ "explain_file" ] }, { "page": "explain_known_files", "title": "Names of all morie output CSVs with registered explanations", "topics": [ "explain_known_files" ] }, { "page": "extenders_nonparam", "title": "FDR / nonparametric / quantile / latent-class extenders (Phase 1.n)", "topics": [ "extenders_nonparam" ] }, { "page": "extenders_rdd", "title": "RDD / IRT extenders (Phase 1.l)", "topics": [ "extenders_rdd" ] }, { "page": "extenders_spatial", "title": "Spatial / multivariate / meta-analysis extenders (Phase 1.m)", "topics": [ "extenders_spatial" ] }, { "page": "extenders_stats", "title": "Stats extenders (Phase 1.k)", "topics": [ "extenders_stats" ] }, { "page": "external_validate", "title": "External validation on new data", "topics": [ "external_validate" ] }, { "page": "fairness_cityprofile", "title": "City-agnostic data profiles for the predictive-policing audit", "topics": [ "fairness_cityprofile" ] }, { "page": "fairness_metrics", "title": "Group-disparity metrics for auditing classification systems", "topics": [ "fairness_metrics" ] }, { "page": "fairness_temporal", "title": "Multi-city temporal disparity audit", "topics": [ "fairness_temporal" ] }, { "page": "fallback_procedure", "title": "Fallback (fixed-sequence with alpha spending)", "topics": [ "fallback_procedure" ] }, { "page": "fisher_combined", "title": "Fisher's method for combining independent p-values", "topics": [ "fisher_combined" ] }, { "page": "fisher_exact_test", "title": "Fisher's exact test for a 2x2 table", "topics": [ "fisher_exact_test" ] }, { "page": "fixed_effects_meta", "title": "Fixed-effects (inverse-variance) meta-analytic pooling", "topics": [ "fixed_effects_meta" ] }, { "page": "fixed_sequence", "title": "Fixed-sequence (predetermined order) testing", "topics": [ "fixed_sequence" ] }, { "page": "format_dataframe", "title": "Apply uniform formatting to numeric columns", "topics": [ "format_dataframe" ] }, { "page": "format_number", "title": "Format a single number according to style conventions", "topics": [ "format_number" ] }, { "page": "friedman_test", "title": "Friedman test (repeated-measures rank ANOVA)", "topics": [ "friedman_test" ] }, { "page": "frns_metrics", "title": "Group-disparity metrics for auditing classification and risk systems", "topics": [ "frns_metrics" ] }, { "page": "frns_predpol", "title": "Generalised predictive-policing disparity audit", "topics": [ "frns_predpol" ] }, { "page": "frns_temporal", "title": "Multi-city temporal disparity audit", "topics": [ "frns_temporal" ] }, { "page": "full_diagnostics", "title": "Full diagnostic report", "topics": [ "full_diagnostics" ] }, { "page": "gam_smoother", "title": "Thin-plate spline smoother via mgcv::gam", "topics": [ "gam_smoother" ] }, { "page": "glass_delta", "title": "Glass's delta — control-group SD denominator", "topics": [ "glass_delta" ] }, { "page": "harmonic_mean_p", "title": "Harmonic mean p-value", "topics": [ "harmonic_mean_p" ] }, { "page": "hazard_ratio_table", "title": "Hazard-ratio table from Cox model components", "topics": [ "hazard_ratio_table" ] }, { "page": "hcepst", "title": "Complex cepstrum with phase unwrapping", "topics": [ "hcepst" ] }, { "page": "hdecon", "title": "Homomorphic deconvolution via cepstral liftering", "topics": [ "hdecon" ] }, { "page": "hfd", "title": "Higuchi fractal dimension", "topics": [ "hfd" ] }, { "page": "hierarchical_bonferroni", "title": "Hierarchical (serial gatekeeping) Bonferroni procedure", "topics": [ "hierarchical_bonferroni" ] }, { "page": "hochberg", "title": "Hochberg step-up FWER procedure", "topics": [ "hochberg" ] }, { "page": "holm", "title": "Holm step-down FWER procedure", "topics": [ "holm" ] }, { "page": "holm_sidak", "title": "Holm-Sidak step-down procedure", "topics": [ "holm_sidak" ] }, { "page": "hommel", "title": "Hommel FWER procedure", "topics": [ "hommel" ] }, { "page": "hosmer_lemeshow_test", "title": "Hosmer-Lemeshow goodness-of-fit test for logistic regression", "topics": [ "hosmer_lemeshow_test" ] }, { "page": "hrvfd", "title": "HRV frequency-domain metrics (VLF, LF, HF, LF/HF)", "topics": [ "hrvfd" ] }, { "page": "hrvnl", "title": "HRV nonlinear metrics (Poincare SD1, SD2)", "topics": [ "hrvnl" ] }, { "page": "hrvtd", "title": "HRV time-domain metrics (SDNN, RMSSD, pNN50)", "topics": [ "hrvtd" ] }, { "page": "i_squared", "title": "I^2 heterogeneity statistic (Higgins)", "topics": [ "i_squared" ] }, { "page": "incidence_rate_difference", "title": "Incidence rate difference (IRD)", "topics": [ "incidence_rate_difference" ] }, { "page": "intraclass_correlation", "title": "Intraclass correlation coefficient (Shrout & Fleiss 1979)", "topics": [ "intraclass_correlation" ] }, { "page": "jackknife", "title": "Delete-one (leave-one-out) jackknife", "topics": [ "jackknife" ] }, { "page": "kde", "title": "Kernel density estimation", "topics": [ "kde" ] }, { "page": "kendall_correlation", "title": "Kendall's tau-b correlation", "topics": [ "kendall_correlation" ] }, { "page": "kernel_cond_moments", "title": "Kernel-weighted conditional mean and variance", "topics": [ "kernel_cond_moments" ] }, { "page": "kernel_eval", "title": "Evaluate a kernel function at point u", "topics": [ "kernel_eval" ] }, { "page": "kernel-codes", "title": "Kernel type integer codes", "topics": [ "kernel-codes", "KERNEL_BIWEIGHT", "KERNEL_EPANECHNIKOV", "KERNEL_GAUSSIAN", "KERNEL_TRIANGULAR", "KERNEL_UNIFORM" ] }, { "page": "kfd", "title": "Katz fractal dimension", "topics": [ "kfd" ] }, { "page": "ks_test_one_sample", "title": "One-sample Kolmogorov-Smirnov test", "topics": [ "ks_test_one_sample" ] }, { "page": "ks_test_two_sample", "title": "Two-sample Kolmogorov-Smirnov test", "topics": [ "ks_test_two_sample" ] }, { "page": "leave_one_out_cv", "title": "Leave-one-out cross-validation", "topics": [ "leave_one_out_cv" ] }, { "page": "levene_test", "title": "Levene's test for equality of variances", "topics": [ "levene_test" ] }, { "page": "license_check", "title": "Runtime license-compatibility guard for morie", "topics": [ "license_check" ] }, { "page": "likelihood_ratio_test", "title": "Likelihood ratio test for nested models", "topics": [ "likelihood_ratio_test" ] }, { "page": "lilliefors_test", "title": "Lilliefors test for normality", "topics": [ "lilliefors_test" ] }, { "page": "link_test", "title": "Pregibon link test", "topics": [ "link_test" ] }, { "page": "local_fdr", "title": "Local false discovery rate via empirical-Bayes two-component mixture", "topics": [ "local_fdr" ] }, { "page": "local_linear", "title": "Local linear kernel regression", "topics": [ "local_linear" ] }, { "page": "longitudinal_sim", "title": "Synchronised longitudinal-panel simulation (R parity)", "topics": [ "longitudinal_sim" ] }, { "page": "loocv_bandwidth", "title": "Leave-one-out cross-validation bandwidth for NW regression", "topics": [ "loocv_bandwidth" ] }, { "page": "mann_whitney_u", "title": "Mann-Whitney U / Wilcoxon rank-sum test", "topics": [ "mann_whitney_u" ] }, { "page": "manski_bounds", "title": "Manski worst-case bounds for the ATE", "topics": [ "manski_bounds" ] }, { "page": "mcnemar_test", "title": "McNemar's test (paired nominal data)", "topics": [ "mcnemar_test" ] }, { "page": "midranks", "title": "Midrank vector with tie summary (Gibbons Ch 5.6.2)", "topics": [ "midranks" ] }, { "page": "model_comparison_table", "title": "Compare multiple model fits on AIC, BIC, log-likelihood and (optional) LR tests", "topics": [ "model_comparison_table" ] }, { "page": "morie_anominate_ideal_points", "title": "Alpha-NOMINATE ideal-point estimation via 'anominate'", "topics": [ "morie_anominate_ideal_points" ] }, { "page": "morie_anova_one_way", "title": "One-way ANOVA", "topics": [ "morie_anova_one_way" ] }, { "page": "morie_arch_in_mean", "title": "ARCH(1)-in-mean model", "topics": [ "morie_arch_in_mean" ] }, { "page": "morie_arsau_analyze_aggregate_summary", "title": "Analysis of the ARSAU aggregate-summary-by-year file (2020-2022).", "topics": [ "morie_arsau_analyze_aggregate_summary" ] }, { "page": "morie_arsau_analyze_detailed_dataset", "title": "Wide-format analysis of the 2020-2022 detailed-incident dataset.", "topics": [ "morie_arsau_analyze_detailed_dataset" ] }, { "page": "morie_arsau_analyze_individual_records", "title": "End-to-end analysis of the ARSAU individual_records CSV for one year.", "topics": [ "morie_arsau_analyze_individual_records" ] }, { "page": "morie_arsau_analyze_main_records", "title": "End-to-end analysis of the ARSAU main_records CSV for one year.", "topics": [ "morie_arsau_analyze_main_records" ] }, { "page": "morie_arsau_analyze_probe_cycle_records", "title": "Analysis of ARSAU probe_cycle_records (CEW telemetry).", "topics": [ "morie_arsau_analyze_probe_cycle_records" ] }, { "page": "morie_arsau_analyze_weapon_records", "title": "Analysis of ARSAU weapon_records.", "topics": [ "morie_arsau_analyze_weapon_records" ] }, { "page": "morie_arsau_available_datasets", "title": "List ARSAU dataset kinds, optionally restricted to one year.", "topics": [ "morie_arsau_available_datasets" ] }, { "page": "morie_arsau_available_years", "title": "List ARSAU year / year-range buckets.", "topics": [ "morie_arsau_available_years" ] }, { "page": "morie_arsau_ckan_url", "title": "Build the upstream CKAN 'datastore_search' URL for a registry entry.", "topics": [ "morie_arsau_ckan_url" ] }, { "page": "morie_arsau_describe", "title": "Describe a single ARSAU dataset entry.", "topics": [ "morie_arsau_describe" ] }, { "page": "morie_arsau_download", "title": "Bulk-download every ARSAU CSV + sidecar from the upstream Catalogue.", "topics": [ "morie_arsau_download" ] }, { "page": "morie_arsau_fetch_sidecar", "title": "Fetch the CKAN sidecar JSON for a registry entry.", "topics": [ "morie_arsau_fetch_sidecar" ] }, { "page": "morie_arsau_load_aggregate_summary", "title": "Load ARSAU aggregate-summary-by-year CSV (2020-2022 only).", "topics": [ "morie_arsau_load_aggregate_summary" ] }, { "page": "morie_arsau_load_detailed_dataset", "title": "Load ARSAU detailed-incident-level CSV (2020-2022 only).", "topics": [ "morie_arsau_load_detailed_dataset" ] }, { "page": "morie_arsau_load_individual_records", "title": "Load ARSAU individual_records CSV.", "topics": [ "morie_arsau_load_individual_records" ] }, { "page": "morie_arsau_load_main_records", "title": "Load ARSAU main_records CSV for the given year.", "topics": [ "morie_arsau_load_main_records" ] }, { "page": "morie_arsau_load_probe_cycle_records", "title": "Load ARSAU probe_cycle_records CSV (CEW telemetry).", "topics": [ "morie_arsau_load_probe_cycle_records" ] }, { "page": "morie_arsau_load_weapon_records", "title": "Load ARSAU weapon_records CSV.", "topics": [ "morie_arsau_load_weapon_records" ] }, { "page": "morie_arsau_read_markdown_dictionary", "title": "Read an Ontario-Catalogue Markdown data-dictionary sidecar.", "topics": [ "morie_arsau_read_markdown_dictionary" ] }, { "page": "morie_arsau_read_sidecar", "title": "Read a CKAN datastore_search JSON sidecar.", "topics": [ "morie_arsau_read_sidecar" ] }, { "page": "morie_arsau_read_xlsx_dictionary", "title": "Read an Ontario-Catalogue XLSX data-dictionary sidecar.", "topics": [ "morie_arsau_read_xlsx_dictionary" ] }, { "page": "morie_arsau_registry_df", "title": "ARSAU registry rendered as a tidy 'data.frame'.", "topics": [ "morie_arsau_registry_df" ] }, { "page": "morie_arsau_sidecar_schema", "title": "Extract a simplified '[name, type, notes]' schema from a parsed CKAN sidecar.", "topics": [ "morie_arsau_sidecar_schema" ] }, { "page": "morie_arsau_sidecar_to_frame", "title": "Convert a CKAN sidecar's 'records' array-of-arrays into a 'data.frame'.", "topics": [ "morie_arsau_sidecar_to_frame" ] }, { "page": "morie_audit_all_variables", "title": "Audit both OTIS and ARSAU.", "topics": [ "morie_audit_all_variables" ] }, { "page": "morie_audit_arsau_variables", "title": "Audit every ARSAU variable.", "topics": [ "morie_audit_arsau_variables" ] }, { "page": "morie_audit_otis_variables", "title": "Audit every OTIS variable.", "topics": [ "morie_audit_otis_variables" ] }, { "page": "morie_audit_public_outputs", "title": "Audit declared outputs against files on disk", "topics": [ "morie_audit_public_outputs" ] }, { "page": "morie_bayes_cpi_genomic", "title": "BayesC-pi spike-and-slab variable selection (short Gibbs)", "topics": [ "morie_bayes_cpi_genomic" ] }, { "page": "morie_bayes_ridge_gibbs", "title": "BayesA via short Gibbs sampler (Meuwissen-Hayes-Goddard 2001)", "topics": [ "morie_bayes_ridge_gibbs" ] }, { "page": "morie_bayesian_lasso_full", "title": "Bayesian LASSO (Park & Casella 2008 short Gibbs)", "topics": [ "morie_bayesian_lasso_full" ] }, { "page": "morie_bayesian_ridge_regression", "title": "Bayesian ridge regression (RR-BLUP closed form)", "topics": [ "morie_bayesian_ridge_regression" ] }, { "page": "morie_boot_basic_ci", "title": "Direct bridge to 'boot::boot.ci'", "topics": [ "morie_boot_basic_ci" ] }, { "page": "morie_boot_run", "title": "Direct bridge to 'boot::boot'", "topics": [ "morie_boot_run" ] }, { "page": "morie_bootstrap_sample", "title": "Bootstrap resampling for any statistic", "topics": [ "morie_bootstrap_sample" ] }, { "page": "morie_build_outputs_manifest", "title": "Build an outputs manifest from a directory of artifacts", "topics": [ "morie_build_outputs_manifest" ] }, { "page": "morie_builtin_db", "title": "Get path to the built-in MORIE datasets database", "topics": [ "morie_builtin_db" ] }, { "page": "morie_cache_clear", "title": "Clear morie's persistent cache directory", "topics": [ "morie_cache_clear" ] }, { "page": "morie_cache_dir", "title": "morie cache contract", "topics": [ "morie_cache_dir" ] }, { "page": "morie_cache_file", "title": "Cache local RDS/CSV data into the SQLite database", "topics": [ "morie_cache_file" ] }, { "page": "morie_cache_list", "title": "List all tables in the MORIE cache", "topics": [ "morie_cache_list" ] }, { "page": "morie_cache_load", "title": "Load a table from the MORIE cache", "topics": [ "morie_cache_load" ] }, { "page": "morie_cache_store", "title": "Store a data frame in the MORIE cache", "topics": [ "morie_cache_store" ] }, { "page": "morie_calculate_ebac", "title": "Calculate estimated Blood Alcohol Concentration (eBAC)", "topics": [ "morie_calculate_ebac" ] }, { "page": "morie_calculate_ipw_weights", "title": "Calculate inverse probability of treatment weights (IPTW)", "topics": [ "morie_calculate_ipw_weights" ] }, { "page": "morie_calibration_weights", "title": "Calibration weights via iterative proportional fitting (raking)", "topics": [ "morie_calibration_weights" ] }, { "page": "morie_canonicalize_cpads_data", "title": "Canonicalize raw CPADS PUMF columns", "topics": [ "morie_canonicalize_cpads_data" ] }, { "page": "morie_causal_impact", "title": "Bayesian structural time-series intervention analysis", "topics": [ "morie_causal_impact" ] }, { "page": "morie_causal_robust_se", "title": "Robust / heteroskedasticity-consistent variance for a fitted model", "topics": [ "morie_causal_robust_se" ] }, { "page": "morie_causal_weighting", "title": "Estimate balancing weights via 'WeightIt'", "topics": [ "morie_causal_weighting" ] }, { "page": "morie_check_plugin_license", "title": "Check whether a downstream package's SPDX is GPL-compatible", "topics": [ "morie_check_plugin_license" ] }, { "page": "morie_chi_square_test", "title": "Chi-square test of independence or goodness-of-fit", "topics": [ "morie_chi_square_test" ] }, { "page": "morie_ckan_search", "title": "Search any CKAN open-data portal for datasets", "topics": [ "morie_ckan_search" ] }, { "page": "morie_classify_variable", "title": "Classify one variable.", "topics": [ "morie_classify_variable" ] }, { "page": "morie_cli_dump_catalog", "title": "Emit a unified catalog CSV for the rmorie-cli binary", "topics": [ "morie_cli_dump_catalog" ] }, { "page": "morie_cluster_sample", "title": "Two-stage cluster sampling", "topics": [ "morie_cluster_sample" ] }, { "page": "morie_cnn_genomic", "title": "CNN genomic predictor (Conv1D + GAP + dense, base R)", "topics": [ "morie_cnn_genomic" ] }, { "page": "morie_coherence", "title": "Magnitude-squared morie_coherence between two time series", "topics": [ "morie_coherence" ] }, { "page": "morie_coin_independence", "title": "General independence test via 'coin'", "topics": [ "morie_coin_independence" ] }, { "page": "morie_coin_oneway", "title": "Permutation one-way ANOVA via 'coin'", "topics": [ "morie_coin_oneway" ] }, { "page": "morie_coin_wilcoxon", "title": "Permutation Wilcoxon test via 'coin'", "topics": [ "morie_coin_wilcoxon" ] }, { "page": "morie_compare_nested_logistic_models", "title": "Compare nested logistic-regression models via likelihood-ratio test", "topics": [ "morie_compare_nested_logistic_models" ] }, { "page": "morie_compute_design_weights", "title": "Compute inverse-probability design weights", "topics": [ "morie_compute_design_weights" ] }, { "page": "morie_concordance_incomplete", "title": "Kendall's coefficient of concordance W (Gibbons Ch 12.5)", "topics": [ "morie_concordance_incomplete" ] }, { "page": "morie_confusion_matrix_metrics", "title": "Confusion matrix with precision / recall / F1 (R parity)", "topics": [ "morie_confusion_matrix_metrics" ] }, { "page": "morie_contingency_coefficient", "title": "Pearson contingency coefficient C (Gibbons Ch 14.2.1)", "topics": [ "morie_contingency_coefficient" ] }, { "page": "morie_control_comparison", "title": "Nonparametric many-to-one comparisons to a control (Gibbons Ch 10.7)", "topics": [ "morie_control_comparison" ] }, { "page": "morie_control_median_test", "title": "Mood's median (control-median) test (Gibbons Ch 6.5)", "topics": [ "morie_control_median_test" ] }, { "page": "morie_copula_fit", "title": "Fit a copula by maximum-likelihood via 'copula'", "topics": [ "morie_copula_fit" ] }, { "page": "morie_copula_sample", "title": "Draw a random sample from a copula via 'copula'", "topics": [ "morie_copula_sample" ] }, { "page": "morie_corrections_uof_resource_ids", "title": "Canonical CKAN resource id table for the Corrections UoF dataset.", "topics": [ "morie_corrections_uof_resource_ids" ] }, { "page": "morie_cpads_canonicalize_frame", "title": "Canonicalize raw CPADS PUMF columns into morie's analysis schema.", "topics": [ "morie_cpads_canonicalize_frame" ] }, { "page": "morie_cpads_contract", "title": "Return the CPADS analysis-frame contract.", "topics": [ "morie_cpads_contract" ] }, { "page": "morie_cpads_has_raw_columns", "title": "Detect whether a data frame looks like raw CPADS PUMF data.", "topics": [ "morie_cpads_has_raw_columns" ] }, { "page": "morie_cpads_infer_file_format", "title": "Infer the on-disk file format for a CPADS file path.", "topics": [ "morie_cpads_infer_file_format" ] }, { "page": "morie_cpads_missing_variables", "title": "Identify missing canonical CPADS variables in a column set.", "topics": [ "morie_cpads_missing_variables" ] }, { "page": "morie_cpads_validate_frame", "title": "Validate a data frame against the canonical CPADS analysis contract.", "topics": [ "morie_cpads_validate_frame" ] }, { "page": "morie_crypto_chacha20_poly1305_decrypt", "title": "ChaCha20-Poly1305 IETF authenticated decryption", "topics": [ "morie_crypto_chacha20_poly1305_decrypt" ] }, { "page": "morie_crypto_chacha20_poly1305_encrypt", "title": "ChaCha20-Poly1305 IETF authenticated encryption", "topics": [ "morie_crypto_chacha20_poly1305_encrypt" ] }, { "page": "morie_crypto_hkdf_sha256", "title": "HKDF-SHA256 (RFC 5869)", "topics": [ "morie_crypto_hkdf_sha256" ] }, { "page": "morie_crypto_hybrid_decrypt", "title": "Hybrid decrypt: ML-KEM-768 + ChaCha20-Poly1305", "topics": [ "morie_crypto_hybrid_decrypt" ] }, { "page": "morie_crypto_hybrid_encrypt", "title": "Hybrid encrypt: ML-KEM-768 + ChaCha20-Poly1305", "topics": [ "morie_crypto_hybrid_encrypt" ] }, { "page": "morie_crypto_hybrid_keygen", "title": "Generate an ML-KEM-768 key pair for hybrid encryption", "topics": [ "morie_crypto_hybrid_keygen" ] }, { "page": "morie_crypto_keystore_create", "title": "Create a new empty morie keystore", "topics": [ "morie_crypto_keystore_create" ] }, { "page": "morie_crypto_keystore_list", "title": "List key names in the morie keystore", "topics": [ "morie_crypto_keystore_list" ] }, { "page": "morie_crypto_keystore_load", "title": "Load a key pair from the morie keystore", "topics": [ "morie_crypto_keystore_load" ] }, { "page": "morie_crypto_keystore_store", "title": "Store a key pair in the morie keystore", "topics": [ "morie_crypto_keystore_store" ] }, { "page": "morie_crypto_liboqs_available", "title": "Is liboqs available in this morie build?", "topics": [ "morie_crypto_liboqs_available" ] }, { "page": "morie_crypto_liboqs_version", "title": "liboqs runtime version string", "topics": [ "morie_crypto_liboqs_version" ] }, { "page": "morie_crypto_mldsa65_keygen", "title": "ML-DSA-65 keypair generation (NIST FIPS 204)", "topics": [ "morie_crypto_mldsa65_keygen" ] }, { "page": "morie_crypto_mldsa65_sign", "title": "ML-DSA-65 signature", "topics": [ "morie_crypto_mldsa65_sign" ] }, { "page": "morie_crypto_mldsa65_verify", "title": "ML-DSA-65 signature verification", "topics": [ "morie_crypto_mldsa65_verify" ] }, { "page": "morie_crypto_mlkem768_decaps", "title": "ML-KEM-768 decapsulation", "topics": [ "morie_crypto_mlkem768_decaps" ] }, { "page": "morie_crypto_mlkem768_encaps", "title": "ML-KEM-768 encapsulation", "topics": [ "morie_crypto_mlkem768_encaps" ] }, { "page": "morie_crypto_mlkem768_keygen", "title": "ML-KEM-768 keypair generation (NIST FIPS 203)", "topics": [ "morie_crypto_mlkem768_keygen" ] }, { "page": "morie_crypto_random_bytes", "title": "Cryptographically secure random bytes (libsodium)", "topics": [ "morie_crypto_random_bytes" ] }, { "page": "morie_crypto_sodium_available", "title": "Is libsodium available in this morie build?", "topics": [ "morie_crypto_sodium_available" ] }, { "page": "morie_crypto_sodium_version", "title": "libsodium runtime version string", "topics": [ "morie_crypto_sodium_version" ] }, { "page": "morie_dataset_catalog", "title": "List all datasets in the MORIE catalog", "topics": [ "morie_dataset_catalog" ] }, { "page": "morie_dataset_column_profile", "title": "Build a single-column profile record.", "topics": [ "morie_dataset_column_profile" ] }, { "page": "morie_dataset_detect_role", "title": "Detect the suggested epidemiological role of a column.", "topics": [ "morie_dataset_detect_role" ] }, { "page": "morie_dataset_infer_level", "title": "Infer the Stevens NOIR measurement level for a single vector.", "topics": [ "morie_dataset_infer_level" ] }, { "page": "morie_dataset_info", "title": "Get metadata for a single dataset", "topics": [ "morie_dataset_info" ] }, { "page": "morie_dataset_load", "title": "Load a dataset from a CSV / TSV / Excel / Parquet / JSON file.", "topics": [ "morie_dataset_load" ] }, { "page": "morie_dataset_portal_catalog", "title": "Build the cross-portal dataset catalog", "topics": [ "morie_dataset_portal_catalog" ] }, { "page": "morie_dataset_portal_catalog_clear_cache", "title": "Clear the session-scoped portal-catalog cache", "topics": [ "morie_dataset_portal_catalog_clear_cache" ] }, { "page": "morie_dataset_profile", "title": "Fully profile a data frame without prior schema knowledge.", "topics": [ "morie_dataset_profile" ] }, { "page": "morie_dataset_profile_summary_table", "title": "Render a human-readable dataset profile summary table.", "topics": [ "morie_dataset_profile_summary_table" ] }, { "page": "morie_dataset_profile_to_list", "title": "Serialize a dataset profile to a plain nested list.", "topics": [ "morie_dataset_profile_to_list" ] }, { "page": "morie_dataset_suggest_plan", "title": "Suggest an ordered analysis plan based on a dataset profile.", "topics": [ "morie_dataset_suggest_plan" ] }, { "page": "morie_dataset_summarize_column", "title": "Compute level-appropriate summary statistics for one column.", "topics": [ "morie_dataset_summarize_column" ] }, { "page": "morie_datasets_arcgis_item_by_id", "title": "Generic by-id loader for any ArcGIS Online Feature Service item.", "topics": [ "morie_datasets_arcgis_item_by_id" ] }, { "page": "morie_datasets_arcgis_item_metadata", "title": "Resolve any ArcGIS Online item id to its FeatureServer URL + canonical metadata.", "topics": [ "morie_datasets_arcgis_item_metadata" ] }, { "page": "morie_datasets_arsau_aggregate_summary", "title": "Ontario Use-of-Force aggregate summary (5-year 2020-2022, pre-RBDS rollup)", "topics": [ "morie_datasets_arsau_aggregate_summary" ] }, { "page": "morie_datasets_arsau_detailed_dataset", "title": "Ontario Use-of-Force detailed dataset (5-year 2020-2022, pre-RBDS)", "topics": [ "morie_datasets_arsau_detailed_dataset" ] }, { "page": "morie_datasets_arsau_uof_individual_records", "title": "Ontario Use-of-Force individual records (one row per individual-in-incident)", "topics": [ "morie_datasets_arsau_uof_individual_records" ] }, { "page": "morie_datasets_arsau_uof_main_records", "title": "Ontario Use-of-Force main records (one row per incident)", "topics": [ "morie_datasets_arsau_uof_main_records" ] }, { "page": "morie_datasets_arsau_uof_probe_cycle_records", "title": "Ontario Use-of-Force probe-cycle records (one row per CEW cartridge probe per individual-in-incident)", "topics": [ "morie_datasets_arsau_uof_probe_cycle_records" ] }, { "page": "morie_datasets_arsau_uof_weapon_records", "title": "Ontario Use-of-Force weapon records (one row per weapon per individual-in-incident)", "topics": [ "morie_datasets_arsau_uof_weapon_records" ] }, { "page": "morie_datasets_bigquery", "title": "Pull a BigQuery table (or filtered slice) as a 'data.frame'.", "topics": [ "morie_datasets_bigquery" ] }, { "page": "morie_datasets_browse", "title": "Browse + filter the morie cross-portal dataset catalog", "topics": [ "morie_datasets_browse" ] }, { "page": "morie_datasets_calgary_community_crime_stats", "title": "Calgary Community Crime Statistics (sample)", "topics": [ "morie_datasets_calgary_community_crime_stats", "morie_datasets_calgary_fire_response_calls", "morie_datasets_calgary_fire_stations" ] }, { "page": "morie_datasets_calgary_open_crime_adjacent_layers", "title": "Calgary Open Data crime-adjacent catalog", "topics": [ "morie_datasets_calgary_open_crime_adjacent_layers", "morie_datasets_edmonton_open_crime_adjacent_layers", "morie_datasets_ottawa_open_crime_adjacent_layers" ] }, { "page": "morie_datasets_calgary_socrata_by_id", "title": "Fetch a Calgary Open Data Socrata dataset by ID", "topics": [ "morie_datasets_calgary_socrata_by_id", "morie_datasets_edmonton_socrata_by_id" ] }, { "page": "morie_datasets_chicago_arrests", "title": "City of Chicago Open Data - Arrests feed ('dpt3-jri9')", "topics": [ "morie_datasets_chicago_arrests" ] }, { "page": "morie_datasets_chicago_community_areas", "title": "Chicago Community Area boundaries (cauq-8yn6)", "topics": [ "morie_datasets_chicago_community_areas" ] }, { "page": "morie_datasets_chicago_crime", "title": "City of Chicago \"Crimes - 2001 to Present\" feed ('ijzp-q8t2')", "topics": [ "morie_datasets_chicago_crime" ] }, { "page": "morie_datasets_chicago_crime_map", "title": "City of Chicago \"Crimes - 2001 to Present - Map\" view ('ahwe-kpsy')", "topics": [ "morie_datasets_chicago_crime_map" ] }, { "page": "morie_datasets_chicago_crime_odata", "title": "City of Chicago Crimes feed via OData v4 ('ijzp-q8t2')", "topics": [ "morie_datasets_chicago_crime_odata" ] }, { "page": "morie_datasets_chicago_crime_resolved", "title": "One-call Chicago crime + boundary + dictionary join", "topics": [ "morie_datasets_chicago_crime_resolved" ] }, { "page": "morie_datasets_chicago_crime_soql", "title": "City of Chicago Crimes feed - arbitrary-SoQL escape hatch", "topics": [ "morie_datasets_chicago_crime_soql" ] }, { "page": "morie_datasets_chicago_iucr_codes", "title": "Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) code dictionary (c7ck-438e)", "topics": [ "morie_datasets_chicago_iucr_codes" ] }, { "page": "morie_datasets_chicago_neighborhoods", "title": "Chicago Neighborhoods boundary (Office of Tourism)", "topics": [ "morie_datasets_chicago_neighborhoods" ] }, { "page": "morie_datasets_chicago_police_beats", "title": "Chicago Police Beats (current) boundaries ('n9it-hstw')", "topics": [ "morie_datasets_chicago_police_beats" ] }, { "page": "morie_datasets_chicago_police_districts", "title": "Chicago Police Districts (current) boundaries (24zt-jpfn)", "topics": [ "morie_datasets_chicago_police_districts" ] }, { "page": "morie_datasets_chicago_wards", "title": "Chicago City Council Ward boundaries (sp34-6z76)", "topics": [ "morie_datasets_chicago_wards" ] }, { "page": "morie_datasets_ckan_package", "title": "Pull every CSV resource of a CKAN package as a list of data frames.", "topics": [ "morie_datasets_ckan_package" ] }, { "page": "morie_datasets_ckan_search", "title": "Search a CKAN open-data portal by free-text query.", "topics": [ "morie_datasets_ckan_search" ] }, { "page": "morie_datasets_corrections_uof_ethnic_origin", "title": "Inmate-participant ethnic origin", "topics": [ "morie_datasets_corrections_uof_ethnic_origin" ] }, { "page": "morie_datasets_corrections_uof_incident_type", "title": "Incident-type lookup", "topics": [ "morie_datasets_corrections_uof_incident_type" ] }, { "page": "morie_datasets_corrections_uof_incidents", "title": "Use-of-force incidents (head dataset)", "topics": [ "morie_datasets_corrections_uof_incidents" ] }, { "page": "morie_datasets_corrections_uof_indigenous", "title": "Inmate-participant Indigenous identity", "topics": [ "morie_datasets_corrections_uof_indigenous" ] }, { "page": "morie_datasets_corrections_uof_inmate_incident", "title": "Inmate-to-incidents bridging table", "topics": [ "morie_datasets_corrections_uof_inmate_incident" ] }, { "page": "morie_datasets_corrections_uof_inmate_participant", "title": "Inmate-participant demographics (head)", "topics": [ "morie_datasets_corrections_uof_inmate_participant" ] }, { "page": "morie_datasets_corrections_uof_institution_summary", "title": "Institution-level annual incident summary", "topics": [ "morie_datasets_corrections_uof_institution_summary" ] }, { "page": "morie_datasets_corrections_uof_location_summary", "title": "Location-of-incident annual summary", "topics": [ "morie_datasets_corrections_uof_location_summary" ] }, { "page": "morie_datasets_corrections_uof_race", "title": "Inmate-participant race", "topics": [ "morie_datasets_corrections_uof_race" ] }, { "page": "morie_datasets_corrections_uof_religion", "title": "Inmate-participant religion", "topics": [ "morie_datasets_corrections_uof_religion" ] }, { "page": "morie_datasets_corrections_uof_select_incident_summary", "title": "Select-incident-type annual summary", "topics": [ "morie_datasets_corrections_uof_select_incident_summary" ] }, { "page": "morie_datasets_corrections_uof_staff_incident", "title": "Staff-to-incidents bridging table", "topics": [ "morie_datasets_corrections_uof_staff_incident" ] }, { "page": "morie_datasets_cpads", "title": "Load the Canadian Postsecondary Alcohol and Drug-use Survey (CPADS)", "topics": [ "morie_datasets_cpads" ] }, { "page": "morie_datasets_cpd_public_arrests", "title": "Chicago Police Department - Public Arrest Data (2014-2017)", "topics": [ "morie_datasets_cpd_public_arrests" ] }, { "page": "morie_datasets_edmonton_police_stations", "title": "Edmonton Police Station locations", "topics": [ "morie_datasets_edmonton_fire_stations", "morie_datasets_edmonton_police_stations" ] }, { "page": "morie_datasets_external_socrata_layers", "title": "List the external Socrata datasets wrapped by morie", "topics": [ "morie_datasets_external_socrata_layers" ] }, { "page": "morie_datasets_load_by_key", "title": "Load a dataset by its cross-portal catalog 'dataset_key'", "topics": [ "morie_datasets_load_by_key" ] }, { "page": "morie_datasets_montreal_ckan_resource", "title": "Fetch records from any donnees.montreal.ca CKAN datastore resource", "topics": [ "morie_datasets_montreal_ckan_resource" ] }, { "page": "morie_datasets_montreal_justice_safety_layers", "title": "Donnees Montreal \"Loi, justice et securite publique\" catalog", "topics": [ "morie_datasets_montreal_justice_safety_layers" ] }, { "page": "morie_datasets_montreal_sim_intervention_types", "title": "SIM intervention TYPE -> French description dictionary", "topics": [ "morie_datasets_montreal_sim_intervention_types" ] }, { "page": "morie_datasets_montreal_sim_interventions", "title": "SIM Montreal Fire Service intervention records (sample)", "topics": [ "morie_datasets_montreal_sim_interventions" ] }, { "page": "morie_datasets_namus_missing_persons", "title": "NamUs missing-persons case metadata.", "topics": [ "morie_datasets_namus_missing_persons" ] }, { "page": "morie_datasets_nibrs", "title": "FBI NIBRS offence-event records via the Crime Data Explorer API.", "topics": [ "morie_datasets_nibrs" ] }, { "page": "morie_datasets_nist_rds", "title": "NIST Reference Datasets (RDS) catalog metadata.", "topics": [ "morie_datasets_nist_rds" ] }, { "page": "morie_datasets_nyc_boroughs", "title": "NYC Borough Boundaries ('gthc-hcne')", "topics": [ "morie_datasets_nyc_boroughs" ] }, { "page": "morie_datasets_nyc_boundaries_catalog", "title": "Unified catalog of NYC OpenData boundary loaders", "topics": [ "morie_datasets_nyc_boundaries_catalog" ] }, { "page": "morie_datasets_nyc_community_districts", "title": "NYC community district boundaries", "topics": [ "morie_datasets_nyc_community_districts" ] }, { "page": "morie_datasets_nyc_council_districts", "title": "NYC City Council district boundaries", "topics": [ "morie_datasets_nyc_council_districts" ] }, { "page": "morie_datasets_nyc_ntas_2020", "title": "NYC Neighborhood Tabulation Areas (2020)", "topics": [ "morie_datasets_nyc_ntas_2020" ] }, { "page": "morie_datasets_nyc_nypd_arrests_historic", "title": "NYPD Arrests Data (Historic)", "topics": [ "morie_datasets_nyc_nypd_arrests_historic" ] }, { "page": "morie_datasets_nyc_nypd_arrests_ytd", "title": "NYPD Arrest Data (Year to Date)", "topics": [ "morie_datasets_nyc_nypd_arrests_ytd" ] }, { "page": "morie_datasets_nyc_nypd_boro_crosswalk", "title": "NYPD borough-code cross-reference (1-letter / UPPER / numeric)", "topics": [ "morie_datasets_nyc_nypd_boro_crosswalk" ] }, { "page": "morie_datasets_nyc_nypd_by_key", "title": "Generic NYC NYPD dataset loader by registry key", "topics": [ "morie_datasets_nyc_nypd_by_key" ] }, { "page": "morie_datasets_nyc_nypd_complaint_historic", "title": "NYPD Complaint Data Historic", "topics": [ "morie_datasets_nyc_nypd_complaint_historic" ] }, { "page": "morie_datasets_nyc_nypd_complaint_ytd", "title": "NYPD Complaint Data Current (Year To Date)", "topics": [ "morie_datasets_nyc_nypd_complaint_ytd" ] }, { "page": "morie_datasets_nyc_nypd_hate_crimes", "title": "NYPD Hate Crimes", "topics": [ "morie_datasets_nyc_nypd_hate_crimes" ] }, { "page": "morie_datasets_nyc_nypd_law_books", "title": "NYS / NYC statute book code dictionary", "topics": [ "morie_datasets_nyc_nypd_law_books" ] }, { "page": "morie_datasets_nyc_nypd_layers", "title": "List the NYPD criminal-justice Socrata datasets wrapped by morie", "topics": [ "morie_datasets_nyc_nypd_layers" ] }, { "page": "morie_datasets_nyc_nypd_offense_codes", "title": "NYPD offense-code dictionary ('ky_cd' + 'pd_cd' + descriptions)", "topics": [ "morie_datasets_nyc_nypd_offense_codes" ] }, { "page": "morie_datasets_nyc_nypd_resolved", "title": "One-call NYPD data + borough + precinct join", "topics": [ "morie_datasets_nyc_nypd_resolved" ] }, { "page": "morie_datasets_nyc_nypd_uof_incidents", "title": "NYPD Use of Force Incidents", "topics": [ "morie_datasets_nyc_nypd_uof_incidents" ] }, { "page": "morie_datasets_nyc_nypd_uof_subjects", "title": "NYPD Use of Force: Subjects", "topics": [ "morie_datasets_nyc_nypd_uof_subjects" ] }, { "page": "morie_datasets_nyc_nypd_vehicle_stops", "title": "NYPD Vehicle Stop Reports", "topics": [ "morie_datasets_nyc_nypd_vehicle_stops" ] }, { "page": "morie_datasets_nyc_opendata_bulk_layers", "title": "NYC OpenData bulk catalog (2851 entities)", "topics": [ "morie_datasets_calgary_opendata_bulk_layers", "morie_datasets_chicago_opendata_bulk_layers", "morie_datasets_edmonton_opendata_bulk_layers", "morie_datasets_montreal_opendata_bulk_layers", "morie_datasets_nyc_opendata_bulk_layers", "morie_datasets_ottawa_opendata_bulk_layers", "morie_datasets_toronto_opendata_bulk_layers", "morie_datasets_vancouver_opendata_bulk_layers" ] }, { "page": "morie_datasets_nyc_police_precincts", "title": "NYC Police Precincts boundary layer ('y76i-bdw7')", "topics": [ "morie_datasets_nyc_police_precincts" ] }, { "page": "morie_datasets_nyc_school_districts", "title": "NYC public school district boundaries (NYS K-12)", "topics": [ "morie_datasets_nyc_school_districts" ] }, { "page": "morie_datasets_nyc_socrata_by_id", "title": "Fetch a NYC OpenData Socrata dataset by ID", "topics": [ "morie_datasets_chicago_socrata_by_id", "morie_datasets_nyc_socrata_by_id" ] }, { "page": "morie_datasets_nyc_stop_and_frisk", "title": "NYPD Stop, Question and Frisk (SQF) microdata via NYC OpenData.", "topics": [ "morie_datasets_nyc_stop_and_frisk" ] }, { "page": "morie_datasets_nyc_zctas", "title": "NYC ZIP Code Tabulation Areas (ZCTAs)", "topics": [ "morie_datasets_nyc_zctas" ] }, { "page": "morie_datasets_ontario_ckan_by_key", "title": "Generic Ontario CKAN dataset loader (by registry key)", "topics": [ "morie_datasets_ontario_ckan_by_key" ] }, { "page": "morie_datasets_ontario_ckan_layers", "title": "List the Ontario CKAN datasets wrapped by morie", "topics": [ "morie_datasets_ontario_ckan_layers" ] }, { "page": "morie_datasets_otis_a01", "title": "Load the OTIS A01 Restrictive-Confinement Detailed Dataset", "topics": [ "morie_datasets_otis_a01" ] }, { "page": "morie_datasets_otis_a01_restrictive_confinement", "title": "OTIS a01 - Restrictive Confinement (detailed per-individual)", "topics": [ "morie_datasets_otis_a01_restrictive_confinement" ] }, { "page": "morie_datasets_otis_b01_segregation_detailed", "title": "OTIS b01 - Segregation detailed (per-individual episodes)", "topics": [ "morie_datasets_otis_b01_segregation_detailed" ] }, { "page": "morie_datasets_otis_b02_segregation_total_days", "title": "OTIS b02 - Segregation total days per individual", "topics": [ "morie_datasets_otis_b02_segregation_total_days" ] }, { "page": "morie_datasets_otis_b03_seg_alerts_by_institution", "title": "OTIS b03 - Segregation placements: alerts + hold by institution", "topics": [ "morie_datasets_otis_b03_seg_alerts_by_institution" ] }, { "page": "morie_datasets_otis_b04_seg_consecutive_by_region", "title": "OTIS b04 - Segregation consecutive durations by region", "topics": [ "morie_datasets_otis_b04_seg_consecutive_by_region" ] }, { "page": "morie_datasets_otis_b05_seg_consecutive_lengths", "title": "OTIS b05 - Segregation placements by consecutive-length bucket", "topics": [ "morie_datasets_otis_b05_seg_consecutive_lengths" ] }, { "page": "morie_datasets_otis_b06_seg_reason_by_institution", "title": "OTIS b06 - Segregation placements: reason for placement by institution", "topics": [ "morie_datasets_otis_b06_seg_reason_by_institution" ] }, { "page": "morie_datasets_otis_b07_seg_alerts_by_gender", "title": "OTIS b07 - Segregation placements: alerts + hold by gender", "topics": [ "morie_datasets_otis_b07_seg_alerts_by_gender" ] }, { "page": "morie_datasets_otis_b08_seg_consecutive_by_institution", "title": "OTIS b08 - Segregation consecutive durations by institution", "topics": [ "morie_datasets_otis_b08_seg_consecutive_by_institution" ] }, { "page": "morie_datasets_otis_b09_seg_n_times", "title": "OTIS b09 - Individuals in segregation by number of times placed", "topics": [ "morie_datasets_otis_b09_seg_n_times" ] }, { "page": "morie_datasets_otis_c01_individuals_total", "title": "OTIS c01 - Total individuals (in custody / restrictive confinement / segregation)", "topics": [ "morie_datasets_otis_c01_individuals_total" ] }, { "page": "morie_datasets_otis_c02_individuals_by_institution", "title": "OTIS c02 - Individuals by institution", "topics": [ "morie_datasets_otis_c02_individuals_by_institution" ] }, { "page": "morie_datasets_otis_c03_individuals_race_by_gender", "title": "OTIS c03 - Individuals by race x gender", "topics": [ "morie_datasets_otis_c03_individuals_race_by_gender" ] }, { "page": "morie_datasets_otis_c04_individuals_race_by_region", "title": "OTIS c04 - Individuals by race x region", "topics": [ "morie_datasets_otis_c04_individuals_race_by_region" ] }, { "page": "morie_datasets_otis_c05_individuals_religion_by_region", "title": "OTIS c05 - Individuals by religion x region", "topics": [ "morie_datasets_otis_c05_individuals_religion_by_region" ] }, { "page": "morie_datasets_otis_c06_individuals_age_by_region", "title": "OTIS c06 - Individuals by age category x region", "topics": [ "morie_datasets_otis_c06_individuals_age_by_region" ] }, { "page": "morie_datasets_otis_c07_individuals_alerts", "title": "OTIS c07 - Individuals: alerts + hold flags", "topics": [ "morie_datasets_otis_c07_individuals_alerts" ] }, { "page": "morie_datasets_otis_c08_individuals_religion_by_gender", "title": "OTIS c08 - Individuals by religion x gender", "topics": [ "morie_datasets_otis_c08_individuals_religion_by_gender" ] }, { "page": "morie_datasets_otis_c09_individuals_age_by_gender", "title": "OTIS c09 - Individuals by age category x gender", "topics": [ "morie_datasets_otis_c09_individuals_age_by_gender" ] }, { "page": "morie_datasets_otis_c10_aggregate_durations_by_institution", "title": "OTIS c10 - Aggregate durations by institution", "topics": [ "morie_datasets_otis_c10_aggregate_durations_by_institution" ] }, { "page": "morie_datasets_otis_c11_aggregate_lengths", "title": "OTIS c11 - Aggregate lengths", "topics": [ "morie_datasets_otis_c11_aggregate_lengths" ] }, { "page": "morie_datasets_otis_c12_aggregate_durations_by_region", "title": "OTIS c12 - Aggregate durations by region", "topics": [ "morie_datasets_otis_c12_aggregate_durations_by_region" ] }, { "page": "morie_datasets_otis_d01_deaths_in_custody", "title": "OTIS Deaths-in-Custody detailed dataset (d01)", "topics": [ "morie_datasets_otis_d01_deaths_in_custody" ] }, { "page": "morie_datasets_otis_d02_deaths_by_gender", "title": "OTIS d02 - Deaths in custody by gender", "topics": [ "morie_datasets_otis_d02_deaths_by_gender" ] }, { "page": "morie_datasets_otis_d03_deaths_by_race", "title": "OTIS d03 - Deaths in custody by race", "topics": [ "morie_datasets_otis_d03_deaths_by_race" ] }, { "page": "morie_datasets_otis_d04_deaths_by_religion", "title": "OTIS d04 - Deaths in custody by religion", "topics": [ "morie_datasets_otis_d04_deaths_by_religion" ] }, { "page": "morie_datasets_otis_d05_deaths_by_age_category", "title": "OTIS d05 - Deaths in custody by age category", "topics": [ "morie_datasets_otis_d05_deaths_by_age_category" ] }, { "page": "morie_datasets_otis_d06_cause_by_alert", "title": "OTIS d06 - Deaths in custody by alert type x institution", "topics": [ "morie_datasets_otis_d06_cause_by_alert" ] }, { "page": "morie_datasets_otis_d07_alerts_by_housing_unit", "title": "OTIS d07 - Deaths in custody alerts x housing unit", "topics": [ "morie_datasets_otis_d07_alerts_by_housing_unit" ] }, { "page": "morie_datasets_siu_director_reports", "title": "SIU director's-reports index (legacy PDF anchors).", "topics": [ "morie_datasets_siu_director_reports" ] }, { "page": "morie_datasets_siu_report_fields", "title": "Extract structured fields from an SIU director's-report text or URL.", "topics": [ "morie_datasets_siu_report_fields" ] }, { "page": "morie_datasets_siu_report_text", "title": "Download an SIU director's-report PDF and return its plain text.", "topics": [ "morie_datasets_siu_report_text" ] }, { "page": "morie_datasets_statcan_ccjs_cubes", "title": "Statistics Canada CCJS cube registry (curated subset)", "topics": [ "morie_datasets_statcan_ccjs_cubes" ] }, { "page": "morie_datasets_statcan_cube_metadata", "title": "Fetch a StatCan cube's metadata (dimensions + members) via WDS", "topics": [ "morie_datasets_statcan_cube_metadata" ] }, { "page": "morie_datasets_statcan_full_csv_url", "title": "Get the bulk-CSV download URL for a StatCan cube", "topics": [ "morie_datasets_statcan_full_csv_url" ] }, { "page": "morie_datasets_statcan_vectors", "title": "Fetch the latest N periods for a set of StatCan vectors via WDS", "topics": [ "morie_datasets_statcan_vectors" ] }, { "page": "morie_datasets_summary", "title": "Tally the cross-portal catalog by source + api_mode", "topics": [ "morie_datasets_summary" ] }, { "page": "morie_datasets_toronto_ambulance_stations", "title": "Toronto Ambulance station locations", "topics": [ "morie_datasets_toronto_ambulance_stations" ] }, { "page": "morie_datasets_toronto_asr_miscellaneous", "title": "TPS Annual Statistical Report - Miscellaneous data (aggregated)", "topics": [ "morie_datasets_toronto_asr_miscellaneous" ] }, { "page": "morie_datasets_toronto_open_ckan_resource", "title": "Fetch records from any open.toronto.ca CKAN resource", "topics": [ "morie_datasets_toronto_open_ckan_resource" ] }, { "page": "morie_datasets_toronto_open_crime_adjacent_layers", "title": "Toronto Open Data crime-adjacent CKAN catalog", "topics": [ "morie_datasets_toronto_open_crime_adjacent_layers" ] }, { "page": "morie_datasets_toronto_zoning_per_neighbourhood", "title": "Toronto Zoning per Neighbourhood (EsriCanadaEducation)", "topics": [ "morie_datasets_toronto_zoning_per_neighbourhood" ] }, { "page": "morie_datasets_tps_2008_firs", "title": "2008 FIRS", "topics": [ "morie_datasets_tps_2008_firs" ] }, { "page": "morie_datasets_tps_2009_firs", "title": "2009 FIRS", "topics": [ "morie_datasets_tps_2009_firs" ] }, { "page": "morie_datasets_tps_2010_firs", "title": "2010 FIRS", "topics": [ "morie_datasets_tps_2010_firs" ] }, { "page": "morie_datasets_tps_2011_firs", "title": "2011 FIRS", "topics": [ "morie_datasets_tps_2011_firs" ] }, { "page": "morie_datasets_tps_2012_firs", "title": "2012 FIRS", "topics": [ "morie_datasets_tps_2012_firs" ] }, { "page": "morie_datasets_tps_2013_firs", "title": "2013 FIRS", "topics": [ "morie_datasets_tps_2013_firs" ] }, { "page": "morie_datasets_tps_administrative", "title": "Administrative (ASR-AD-TBL-001)", "topics": [ "morie_datasets_tps_administrative" ] }, { "page": "morie_datasets_tps_arcgis_hub_by_id", "title": "Generic TPS ArcGIS Hub dataset loader by hub_id", "topics": [ "morie_datasets_tps_arcgis_hub_by_id" ] }, { "page": "morie_datasets_tps_arcgis_hub_download", "title": "Direct multi-format downloader (binary or text) for a TPS Hub item", "topics": [ "morie_datasets_tps_arcgis_hub_download" ] }, { "page": "morie_datasets_tps_arcgis_hub_layers", "title": "List the Toronto Police Service ArcGIS Hub datasets wrapped by morie", "topics": [ "morie_datasets_tps_arcgis_hub_layers" ] }, { "page": "morie_datasets_tps_arrested_and_charged_persons", "title": "Arrested and Charged Persons (ASR-ENF-TBL-001)", "topics": [ "morie_datasets_tps_arrested_and_charged_persons" ] }, { "page": "morie_datasets_tps_arrests_and_strip_searches", "title": "Arrests and Strip Searches (RBDC-ARR-TBL-001)", "topics": [ "morie_datasets_tps_arrests_and_strip_searches" ] }, { "page": "morie_datasets_tps_assault", "title": "TPS PSDP - Assault", "topics": [ "morie_datasets_tps_assault" ] }, { "page": "morie_datasets_tps_automobile_ksi", "title": "Automobile KSI", "topics": [ "morie_datasets_tps_automobile_ksi" ] }, { "page": "morie_datasets_tps_autotheft", "title": "TPS PSDP - Auto Theft", "topics": [ "morie_datasets_tps_autotheft" ] }, { "page": "morie_datasets_tps_bicycle_thefts", "title": "Bicycle Thefts Open Data", "topics": [ "morie_datasets_tps_bicycle_thefts" ] }, { "page": "morie_datasets_tps_bicycletheft", "title": "TPS PSDP - Bicycle Theft", "topics": [ "morie_datasets_tps_bicycletheft" ] }, { "page": "morie_datasets_tps_breakandenter", "title": "TPS PSDP - Break and Enter", "topics": [ "morie_datasets_tps_breakandenter" ] }, { "page": "morie_datasets_tps_budget_2020", "title": "Budget_2020", "topics": [ "morie_datasets_tps_budget_2020" ] }, { "page": "morie_datasets_tps_budget_2021", "title": "Budget_2021", "topics": [ "morie_datasets_tps_budget_2021" ] }, { "page": "morie_datasets_tps_budget_2022", "title": "Budget_2022", "topics": [ "morie_datasets_tps_budget_2022" ] }, { "page": "morie_datasets_tps_budget_2023", "title": "Budget_2023", "topics": [ "morie_datasets_tps_budget_2023" ] }, { "page": "morie_datasets_tps_budget_2024", "title": "Budget_2024", "topics": [ "morie_datasets_tps_budget_2024" ] }, { "page": "morie_datasets_tps_budget_2025", "title": "Budget_2025", "topics": [ "morie_datasets_tps_budget_2025" ] }, { "page": "morie_datasets_tps_budget_2026", "title": "Budget_2026", "topics": [ "morie_datasets_tps_budget_2026" ] }, { "page": "morie_datasets_tps_budget_by_command", "title": "Budget_by_Command", "topics": [ "morie_datasets_tps_budget_by_command" ] }, { "page": "morie_datasets_tps_calls_for_service_attended", "title": "Calls for Service Attended (ASR-CS-TBL-003)", "topics": [ "morie_datasets_tps_calls_for_service_attended" ] }, { "page": "morie_datasets_tps_community_safety_indicators", "title": "Community Safety Indicators Open Data", "topics": [ "morie_datasets_tps_community_safety_indicators" ] }, { "page": "morie_datasets_tps_complaint_dispositions", "title": "Complaint Dispositions (ASR-PCF-TBL-003)", "topics": [ "morie_datasets_tps_complaint_dispositions" ] }, { "page": "morie_datasets_tps_cyclist_ksi", "title": "Cyclist KSI", "topics": [ "morie_datasets_tps_cyclist_ksi" ] }, { "page": "morie_datasets_tps_dispatched_calls_by_division", "title": "Dispatched Calls by Division (ASR-CS-TBL-001)", "topics": [ "morie_datasets_tps_dispatched_calls_by_division" ] }, { "page": "morie_datasets_tps_facilities", "title": "Facilities", "topics": [ "morie_datasets_tps_facilities" ] }, { "page": "morie_datasets_tps_fatals_ksi", "title": "Fatals KSI", "topics": [ "morie_datasets_tps_fatals_ksi" ] }, { "page": "morie_datasets_tps_firearms_top_calibres", "title": "Firearms Top Calibres (ASR-F-TBL-001)", "topics": [ "morie_datasets_tps_firearms_top_calibres" ] }, { "page": "morie_datasets_tps_gross_expenditures_by_division", "title": "Gross Expenditures by Division (ASR-PB-TBL-001)", "topics": [ "morie_datasets_tps_gross_expenditures_by_division" ] }, { "page": "morie_datasets_tps_gross_operating_budget", "title": "Gross Operating Budget (ASR-PB-TBL-005)", "topics": [ "morie_datasets_tps_gross_operating_budget" ] }, { "page": "morie_datasets_tps_hatecrimes", "title": "TPS PSDP - Hate Crimes", "topics": [ "morie_datasets_tps_hatecrimes" ] }, { "page": "morie_datasets_tps_homicide", "title": "TPS Homicides feed.", "topics": [ "morie_datasets_tps_homicide" ] }, { "page": "morie_datasets_tps_homicides", "title": "TPS PSDP - Homicides", "topics": [ "morie_datasets_tps_homicides" ] }, { "page": "morie_datasets_tps_intimate_partner_family_violence", "title": "TPS PSDP - Intimate Partner and Family Violence", "topics": [ "morie_datasets_tps_intimate_partner_family_violence" ] }, { "page": "morie_datasets_tps_investigated_alleged_misconduct", "title": "Investigated Alleged Misconduct (ASR-PCF-TBL-002)", "topics": [ "morie_datasets_tps_investigated_alleged_misconduct" ] }, { "page": "morie_datasets_tps_killed_and_seriously_injured", "title": "Killed and Seriously Injured", "topics": [ "morie_datasets_tps_killed_and_seriously_injured" ] }, { "page": "morie_datasets_tps_layers", "title": "List the TPS open-data layers bundled with morie.", "topics": [ "morie_datasets_tps_layers" ] }, { "page": "morie_datasets_tps_major_crime", "title": "TPS Major Crime Indicators feed.", "topics": [ "morie_datasets_tps_major_crime" ] }, { "page": "morie_datasets_tps_mha_apprehensions", "title": "TPS Mental Health Act Apprehensions (PSDP)", "topics": [ "morie_datasets_tps_mha_apprehensions" ] }, { "page": "morie_datasets_tps_miscellaneous_calls_for_service", "title": "Miscellaneous Calls for Service (ASR-CS-TBL-002)", "topics": [ "morie_datasets_tps_miscellaneous_calls_for_service" ] }, { "page": "morie_datasets_tps_miscellaneous_data", "title": "Miscellaneous Data (ASR-MISC-TBL-001)", "topics": [ "morie_datasets_tps_miscellaneous_data" ] }, { "page": "morie_datasets_tps_miscellaneous_firearms", "title": "Miscellaneous Firearms (ASR-F-TBL-003)", "topics": [ "morie_datasets_tps_miscellaneous_firearms" ] }, { "page": "morie_datasets_tps_motorcylist_ksi", "title": "Motorcylist KSI", "topics": [ "morie_datasets_tps_motorcylist_ksi" ] }, { "page": "morie_datasets_tps_neighbourhood_crime_rates", "title": "Neighbourhood Crime Rates Open Data", "topics": [ "morie_datasets_tps_neighbourhood_crime_rates" ] }, { "page": "morie_datasets_tps_passenger_ksi", "title": "Passenger KSI", "topics": [ "morie_datasets_tps_passenger_ksi" ] }, { "page": "morie_datasets_tps_patrol_zone", "title": "Patrol Zone", "topics": [ "morie_datasets_tps_patrol_zone" ] }, { "page": "morie_datasets_tps_pedestrian_ksi", "title": "Pedestrian KSI", "topics": [ "morie_datasets_tps_pedestrian_ksi" ] }, { "page": "morie_datasets_tps_personnel_by_command", "title": "Personnel by Command (ASR-PB-TBL-004)", "topics": [ "morie_datasets_tps_personnel_by_command" ] }, { "page": "morie_datasets_tps_personnel_by_rank", "title": "Personnel by Rank (ASR-PB-TBL-002)", "topics": [ "morie_datasets_tps_personnel_by_rank" ] }, { "page": "morie_datasets_tps_personnel_by_rank_by_division", "title": "Personnel by Rank by Division (ASR-PB-TBL-003)", "topics": [ "morie_datasets_tps_personnel_by_rank_by_division" ] }, { "page": "morie_datasets_tps_persons_in_crisis_calls_for_service_attended", "title": "Persons in Crisis Calls for Service Attended Open Data", "topics": [ "morie_datasets_tps_persons_in_crisis_calls_for_service_attended" ] }, { "page": "morie_datasets_tps_police_divisions", "title": "Police Divisions", "topics": [ "morie_datasets_tps_police_divisions" ] }, { "page": "morie_datasets_tps_psdp_resolved", "title": "One-call TPS PSDP data + boundary metadata join", "topics": [ "morie_datasets_tps_psdp_resolved" ] }, { "page": "morie_datasets_tps_regulated_interactions", "title": "Regulated Interactions (ASR-RI-TBL-001)", "topics": [ "morie_datasets_tps_regulated_interactions" ] }, { "page": "morie_datasets_tps_reported_crimes", "title": "Reported Crimes (ASR-RC-TBL-001)", "topics": [ "morie_datasets_tps_reported_crimes" ] }, { "page": "morie_datasets_tps_robbery", "title": "TPS PSDP - Robbery", "topics": [ "morie_datasets_tps_robbery" ] }, { "page": "morie_datasets_tps_search_of_persons", "title": "Search of Persons (ASR-SP-TBL-001)", "topics": [ "morie_datasets_tps_search_of_persons" ] }, { "page": "morie_datasets_tps_shooting_firearm_discharges", "title": "TPS PSDP - Shooting and Firearm Discharges", "topics": [ "morie_datasets_tps_shooting_firearm_discharges" ] }, { "page": "morie_datasets_tps_shootings", "title": "TPS Shootings and Firearm Discharges feed.", "topics": [ "morie_datasets_tps_shootings" ] }, { "page": "morie_datasets_tps_staffing_by_command", "title": "Staffing_by_Command", "topics": [ "morie_datasets_tps_staffing_by_command" ] }, { "page": "morie_datasets_tps_theft_from_motor_vehicle", "title": "TPS PSDP - Theft From Motor Vehicle", "topics": [ "morie_datasets_tps_theft_from_motor_vehicle" ] }, { "page": "morie_datasets_tps_theft_over", "title": "TPS PSDP - Theft Over", "topics": [ "morie_datasets_tps_theft_over" ] }, { "page": "morie_datasets_tps_tickets_issued", "title": "Tickets Issued (ASR-ENF-TBL-002)", "topics": [ "morie_datasets_tps_tickets_issued" ] }, { "page": "morie_datasets_tps_top_20_offences_of_firearm_seizures", "title": "Top 20 Offences of Firearm Seizures (ASR-F-TBL-002)", "topics": [ "morie_datasets_tps_top_20_offences_of_firearm_seizures" ] }, { "page": "morie_datasets_tps_total_public_complaints", "title": "Total Public Complaints (ASR-PCF-TBL-001)", "topics": [ "morie_datasets_tps_total_public_complaints" ] }, { "page": "morie_datasets_tps_traffic_collisions", "title": "Traffic Collisions Open Data (ASR-T-TBL-001)", "topics": [ "morie_datasets_tps_traffic_collisions" ] }, { "page": "morie_datasets_tps_use_of_force_call_for_service_types", "title": "Use of Force: Call for Service Types (RBDC-UOF-TBL-004)", "topics": [ "morie_datasets_tps_use_of_force_call_for_service_types" ] }, { "page": "morie_datasets_tps_use_of_force_call_sources_by_month", "title": "Use of Force: Call Sources by Month (RBDC-UOF-TBL-001)", "topics": [ "morie_datasets_tps_use_of_force_call_sources_by_month" ] }, { "page": "morie_datasets_tps_use_of_force_gender_composition", "title": "Use of Force: Gender Composition (RBDC-UOF-TBL-006)", "topics": [ "morie_datasets_tps_use_of_force_gender_composition" ] }, { "page": "morie_datasets_tps_use_of_force_location_of_occurrences", "title": "Use of Force: Location of Occurrences (RBDC-UOF-TBL-003)", "topics": [ "morie_datasets_tps_use_of_force_location_of_occurrences" ] }, { "page": "morie_datasets_tps_use_of_force_occurrence_category", "title": "Use of Force: Occurrence Category (RBDC-UOF-TBL-005)", "topics": [ "morie_datasets_tps_use_of_force_occurrence_category" ] }, { "page": "morie_datasets_tps_use_of_force_time_of_day_trends", "title": "Use of Force: Time of Day Trends (RBDC-UOF-TBL-002)", "topics": [ "morie_datasets_tps_use_of_force_time_of_day_trends" ] }, { "page": "morie_datasets_tps_use_of_force_use_of_force_types_and_perceived_weapons", "title": "Use of Force: Use of Force Types and Perceived Weapons (RBDC-UOF-TBL-007)", "topics": [ "morie_datasets_tps_use_of_force_use_of_force_types_and_perceived_weapons" ] }, { "page": "morie_datasets_tps_victims_of_crime", "title": "Victims of Crime (ASR-VC-TBL-001)", "topics": [ "morie_datasets_tps_victims_of_crime" ] }, { "page": "morie_datasets_vancouver_opendata_by_id", "title": "Fetch records from a Vancouver Open Data dataset by ID", "topics": [ "morie_datasets_vancouver_opendata_by_id" ] }, { "page": "morie_datasets_vancouver_opendata_layers", "title": "Vancouver Open Data full dataset catalog (Opendatasoft v2.1)", "topics": [ "morie_datasets_vancouver_opendata_layers" ] }, { "page": "morie_datasets_vpd_crime", "title": "Load Vancouver Police Department crime incident data", "topics": [ "morie_datasets_vpd_crime" ] }, { "page": "morie_datasets_vpd_legal_disclaimer", "title": "Read VPD's legal disclaimer (bundled verbatim from the zip)", "topics": [ "morie_datasets_vpd_legal_disclaimer" ] }, { "page": "morie_db_connect", "title": "Connect to the MORIE cache database", "topics": [ "morie_db_connect" ] }, { "page": "morie_db_create_indexes", "title": "Create the recommended B-tree indexes for a morie cache table", "topics": [ "morie_db_create_indexes" ] }, { "page": "morie_dbscan_clustering", "title": "DBSCAN density-based clustering (R parity)", "topics": [ "morie_dbscan_clustering" ] }, { "page": "morie_dcc_multivariate_garch", "title": "DCC multivariate GARCH (Engle 2002)", "topics": [ "morie_dcc_multivariate_garch" ] }, { "page": "morie_decision_tree_split", "title": "Decision tree split (R parity)", "topics": [ "morie_decision_tree_split" ] }, { "page": "morie_deep_learning_genomic", "title": "Single-hidden-layer MLP genomic predictor (base R)", "topics": [ "morie_deep_learning_genomic" ] }, { "page": "morie_default_synthetic_name_map", "title": "Default synthetic-data variable name map", "topics": [ "morie_default_synthetic_name_map" ] }, { "page": "morie_default_workflow_map", "title": "Default workflow step map", "topics": [ "morie_default_workflow_map" ] }, { "page": "morie_desc_atkinson", "title": "Atkinson inequality index via 'DescTools'", "topics": [ "morie_desc_atkinson" ] }, { "page": "morie_desc_cramers_v", "title": "Cramer's V via 'DescTools'", "topics": [ "morie_desc_cramers_v" ] }, { "page": "morie_desc_gini", "title": "Gini coefficient via 'DescTools'", "topics": [ "morie_desc_gini" ] }, { "page": "morie_desc_kappa", "title": "Cohen / Fleiss kappa via 'DescTools'", "topics": [ "morie_desc_kappa" ] }, { "page": "morie_desc_winsorize", "title": "Winsorize a numeric vector via 'DescTools'", "topics": [ "morie_desc_winsorize" ] }, { "page": "morie_describe", "title": "Print the pedagogical narrative for a morie callable.", "topics": [ "morie_describe" ] }, { "page": "morie_describe_by_name", "title": "String-only variant of 'morie_describe'.", "topics": [ "morie_describe_by_name" ] }, { "page": "morie_design_effect", "title": "Design effect (DEFF)", "topics": [ "morie_design_effect" ] }, { "page": "morie_det_rng", "title": "SHA-keyed deterministic RNG for Py<->R parity", "topics": [ "morie_det_rng" ] }, { "page": "morie_det_rng_sha_hex", "title": "SHA-256 hex digest of \"name:seed\" (for Py<->R cross-check)", "topics": [ "morie_det_rng_sha_hex" ] }, { "page": "morie_did_2x2", "title": "Classic 2x2 Difference-in-Differences estimator", "topics": [ "morie_did_2x2" ] }, { "page": "morie_did_aggregate_gt_att", "title": "Aggregate group-time ATTs into summary parameters", "topics": [ "morie_did_aggregate_gt_att" ] }, { "page": "morie_did_bacon_decomposition", "title": "Goodman-Bacon decomposition of the TWFE DiD estimator", "topics": [ "morie_did_bacon_decomposition" ] }, { "page": "morie_did_chaisemartin_dhaultfoeuille", "title": "Heterogeneity-robust DiD (de Chaisemartin & D'Haultfoeuille, 2020)", "topics": [ "morie_did_chaisemartin_dhaultfoeuille" ] }, { "page": "morie_did_continuous_treatment", "title": "DiD with a continuous (dose) treatment", "topics": [ "morie_did_continuous_treatment" ] }, { "page": "morie_did_diagnostics", "title": "Comprehensive diagnostics for a 2x2 DiD setting", "topics": [ "morie_did_diagnostics" ] }, { "page": "morie_did_doubly_robust", "title": "Doubly-robust DiD (Sant'Anna & Zhao, 2020)", "topics": [ "morie_did_doubly_robust" ] }, { "page": "morie_did_event_study", "title": "Event-study DiD specification", "topics": [ "morie_did_event_study" ] }, { "page": "morie_did_fuzzy", "title": "Fuzzy DiD (LATE) via 2SLS", "topics": [ "morie_did_fuzzy" ] }, { "page": "morie_did_group_time_att", "title": "Callaway-Sant'Anna group-time average treatment effects", "topics": [ "morie_did_group_time_att" ] }, { "page": "morie_did_heterogeneous", "title": "Heterogeneity-robust DiD by sub-group / moderator quantile", "topics": [ "morie_did_heterogeneous" ] }, { "page": "morie_did_panel_fe", "title": "Two-way fixed-effects DiD (panel)", "topics": [ "morie_did_panel_fe" ] }, { "page": "morie_did_parallel_trends_data", "title": "Group-by-time outcome means for parallel-trends visualisation", "topics": [ "morie_did_parallel_trends_data" ] }, { "page": "morie_did_placebo_test_group", "title": "Placebo DiD on sub-groups expected to be unaffected", "topics": [ "morie_did_placebo_test_group" ] }, { "page": "morie_did_placebo_test_outcome", "title": "Placebo DiD on outcomes that should be unaffected", "topics": [ "morie_did_placebo_test_outcome" ] }, { "page": "morie_did_placebo_test_time", "title": "Placebo DiD at fake treatment times", "topics": [ "morie_did_placebo_test_time" ] }, { "page": "morie_did_repeated_cross_section", "title": "Repeated cross-section DiD (optionally weighted)", "topics": [ "morie_did_repeated_cross_section" ] }, { "page": "morie_did_sensitivity_analysis", "title": "Sensitivity of DiD estimate to parallel-trends violations", "topics": [ "morie_did_sensitivity_analysis" ] }, { "page": "morie_did_staggered", "title": "Staggered DiD via group-time ATTs with aggregation", "topics": [ "morie_did_staggered" ] }, { "page": "morie_did_synthdid_estimate", "title": "Synthetic DiD via 'synthdid::synthdid_estimate' (explicit-name API)", "topics": [ "morie_did_synthdid_estimate" ] }, { "page": "morie_did_synthetic", "title": "Synthetic Difference-in-Differences (Arkhangelsky et al., 2021)", "topics": [ "morie_did_synthetic" ] }, { "page": "morie_did_test_parallel_trends", "title": "Pre-trend test for parallel trends", "topics": [ "morie_did_test_parallel_trends" ] }, { "page": "morie_did_triple_difference", "title": "Triple-difference (DDD) estimator", "topics": [ "morie_did_triple_difference" ] }, { "page": "morie_did_twoway_fe_weights", "title": "Diagnose TWFE-DiD weights (de Chaisemartin & D'Haultfoeuille, 2020)", "topics": [ "morie_did_twoway_fe_weights" ] }, { "page": "morie_did_wild_cluster_bootstrap", "title": "DiD with wild cluster bootstrap p-values (Cameron-Gelbach-Miller, 2008)", "topics": [ "morie_did_wild_cluster_bootstrap" ] }, { "page": "morie_diffu_diffusion_forward", "title": "DDPM forward (noising) process", "topics": [ "morie_diffu_diffusion_forward" ] }, { "page": "morie_download_bootstrap", "title": "Download bootstrap weight files from CKAN API", "topics": [ "morie_download_bootstrap" ] }, { "page": "morie_dp_gaussian_mixture", "title": "Bayesian nonparametric DP Gaussian mixture via 'dirichletprocess'", "topics": [ "morie_dp_gaussian_mixture" ] }, { "page": "morie_dsp_acf_from_psd", "title": "Autocorrelation from PSD (Wiener-Khinchin)", "topics": [ "morie_dsp_acf_from_psd" ] }, { "page": "morie_dsp_alpha_trimmed_mean", "title": "Alpha-trimmed mean filter", "topics": [ "morie_dsp_alpha_trimmed_mean" ] }, { "page": "morie_dsp_amplitude_histogram", "title": "Amplitude histogram features", "topics": [ "morie_dsp_amplitude_histogram" ] }, { "page": "morie_dsp_arc_length", "title": "Signal arc length", "topics": [ "morie_dsp_arc_length" ] }, { "page": "morie_dsp_band_power", "title": "Bandpower over [f_low, f_high]", "topics": [ "morie_dsp_band_power" ] }, { "page": "morie_dsp_baseline_correlation", "title": "Baseline-corrected Pearson correlation", "topics": [ "morie_dsp_baseline_correlation" ] }, { "page": "morie_dsp_centroidal_time", "title": "Centroidal time", "topics": [ "morie_dsp_centroidal_time" ] }, { "page": "morie_dsp_coherence", "title": "Coherence-squared spectrum", "topics": [ "morie_dsp_coherence" ] }, { "page": "morie_dsp_coherence_spectrum", "title": "Coherence spectrum (alias to morie_dsp_coherence)", "topics": [ "morie_dsp_coherence_spectrum" ] }, { "page": "morie_dsp_comb", "title": "Comb filter built from cascaded notches", "topics": [ "morie_dsp_comb" ] }, { "page": "morie_dsp_complex_cepstrum", "title": "Complex cepstrum", "topics": [ "morie_dsp_complex_cepstrum" ] }, { "page": "morie_dsp_complex_demodulation", "title": "Complex demodulation around a carrier", "topics": [ "morie_dsp_complex_demodulation" ] }, { "page": "morie_dsp_crest_factor", "title": "Crest factor (peak / RMS)", "topics": [ "morie_dsp_crest_factor" ] }, { "page": "morie_dsp_cross_correlation", "title": "Normalised cross-correlation up to a maximum lag", "topics": [ "morie_dsp_cross_correlation" ] }, { "page": "morie_dsp_csd", "title": "Cross-spectral density (Welch)", "topics": [ "morie_dsp_csd" ] }, { "page": "morie_dsp_cv", "title": "Coefficient of variation", "topics": [ "morie_dsp_cv" ] }, { "page": "morie_dsp_derivative_detect", "title": "Derivative-based peak detection", "topics": [ "morie_dsp_derivative_detect" ] }, { "page": "morie_dsp_dicrotic_notch", "title": "Dicrotic-notch detection in pulse waves", "topics": [ "morie_dsp_dicrotic_notch" ] }, { "page": "morie_dsp_ensemble_average", "title": "Ensemble average over fixed-length segments", "topics": [ "morie_dsp_ensemble_average" ] }, { "page": "morie_dsp_entropy_histogram", "title": "Shannon entropy from amplitude histogram", "topics": [ "morie_dsp_entropy_histogram" ] }, { "page": "morie_dsp_even_odd", "title": "Even-odd decomposition of a finite signal", "topics": [ "morie_dsp_even_odd" ] }, { "page": "morie_dsp_fbm_synthesis", "title": "Fractional Brownian motion synthesis (1/f^beta)", "topics": [ "morie_dsp_fbm_synthesis" ] }, { "page": "morie_dsp_form_factor", "title": "Form factor (RMS / mean-absolute)", "topics": [ "morie_dsp_form_factor" ] }, { "page": "morie_dsp_fractal_dim_psd", "title": "Fractal dimension from log-log PSD slope", "topics": [ "morie_dsp_fractal_dim_psd" ] }, { "page": "morie_dsp_hann_filter", "title": "Hann-windowed smoothing filter", "topics": [ "morie_dsp_hann_filter" ] }, { "page": "morie_dsp_higuchi_fd", "title": "Higuchi fractal dimension", "topics": [ "morie_dsp_higuchi_fd" ] }, { "page": "morie_dsp_hilbert_envelope", "title": "Hilbert envelope", "topics": [ "morie_dsp_hilbert_envelope" ] }, { "page": "morie_dsp_hjorth", "title": "All three Hjorth parameters", "topics": [ "morie_dsp_hjorth" ] }, { "page": "morie_dsp_hjorth_activity", "title": "Hjorth activity (variance)", "topics": [ "morie_dsp_hjorth_activity" ] }, { "page": "morie_dsp_hjorth_complexity", "title": "Hjorth complexity", "topics": [ "morie_dsp_hjorth_complexity" ] }, { "page": "morie_dsp_hjorth_mobility", "title": "Hjorth mobility", "topics": [ "morie_dsp_hjorth_mobility" ] }, { "page": "morie_dsp_homomorphic", "title": "Homomorphic high-pass filter", "topics": [ "morie_dsp_homomorphic" ] }, { "page": "morie_dsp_hr_from_rr", "title": "Heart rate from RR intervals (BPM)", "topics": [ "morie_dsp_hr_from_rr" ] }, { "page": "morie_dsp_integrated_emg", "title": "Integrated EMG (sum of absolute values)", "topics": [ "morie_dsp_integrated_emg" ] }, { "page": "morie_dsp_katz_fd", "title": "Katz / box-counting fractal dimension", "topics": [ "morie_dsp_katz_fd" ] }, { "page": "morie_dsp_lms", "title": "LMS adaptive filter (Widrow-Hoff)", "topics": [ "morie_dsp_lms" ] }, { "page": "morie_dsp_matched", "title": "Matched filter (time-reversed template correlator)", "topics": [ "morie_dsp_matched" ] }, { "page": "morie_dsp_mean_abs", "title": "Mean absolute value", "topics": [ "morie_dsp_mean_abs" ] }, { "page": "morie_dsp_mean_frequency", "title": "Mean frequency from PSD", "topics": [ "morie_dsp_mean_frequency" ] }, { "page": "morie_dsp_median_filter", "title": "Median filter", "topics": [ "morie_dsp_median_filter" ] }, { "page": "morie_dsp_median_frequency", "title": "Median frequency from PSD", "topics": [ "morie_dsp_median_frequency" ] }, { "page": "morie_dsp_min_phase", "title": "Minimum-phase correspondent via cepstral folding", "topics": [ "morie_dsp_min_phase" ] }, { "page": "morie_dsp_moving_average", "title": "Moving-average filter (boxcar)", "topics": [ "morie_dsp_moving_average" ] }, { "page": "morie_dsp_myopulse_rate", "title": "Myopulse percentage rate", "topics": [ "morie_dsp_myopulse_rate" ] }, { "page": "morie_dsp_nlms", "title": "NLMS adaptive filter", "topics": [ "morie_dsp_nlms" ] }, { "page": "morie_dsp_notch", "title": "IIR notch filter (single frequency)", "topics": [ "morie_dsp_notch" ] }, { "page": "morie_dsp_onset_detect", "title": "Energy-onset detection", "topics": [ "morie_dsp_onset_detect" ] }, { "page": "morie_dsp_pan_tompkins", "title": "Pan-Tompkins QRS detector", "topics": [ "morie_dsp_pan_tompkins" ] }, { "page": "morie_dsp_parzen_pdf", "title": "Parzen kernel density estimate", "topics": [ "morie_dsp_parzen_pdf" ] }, { "page": "morie_dsp_psd_bartlett", "title": "Bartlett PSD estimate", "topics": [ "morie_dsp_psd_bartlett" ] }, { "page": "morie_dsp_psd_periodogram", "title": "Periodogram PSD estimate", "topics": [ "morie_dsp_psd_periodogram" ] }, { "page": "morie_dsp_psd_to_db", "title": "Convert PSD to decibels", "topics": [ "morie_dsp_psd_to_db" ] }, { "page": "morie_dsp_psd_welch", "title": "Welch PSD estimate (delegated to signal::pwelch / specgram)", "topics": [ "morie_dsp_psd_welch" ] }, { "page": "morie_dsp_qrs_features", "title": "QRS-style waveform descriptors", "topics": [ "morie_dsp_qrs_features" ] }, { "page": "morie_dsp_rls", "title": "RLS adaptive filter", "topics": [ "morie_dsp_rls" ] }, { "page": "morie_dsp_rms", "title": "Root mean square", "topics": [ "morie_dsp_rms" ] }, { "page": "morie_dsp_ruler_fd", "title": "Ruler / divider fractal dimension", "topics": [ "morie_dsp_ruler_fd" ] }, { "page": "morie_dsp_shannon_energy", "title": "Shannon-energy envelope", "topics": [ "morie_dsp_shannon_energy" ] }, { "page": "morie_dsp_shape_factor", "title": "Shape factor (mean-absolute / mean-sqrt-absolute-squared)", "topics": [ "morie_dsp_shape_factor" ] }, { "page": "morie_dsp_slope_sign_changes", "title": "Slope sign changes", "topics": [ "morie_dsp_slope_sign_changes" ] }, { "page": "morie_dsp_snr", "title": "Signal-to-noise ratio estimate (dB)", "topics": [ "morie_dsp_snr" ] }, { "page": "morie_dsp_snr_improvement", "title": "SNR improvement attributable to a filter (dB)", "topics": [ "morie_dsp_snr_improvement" ] }, { "page": "morie_dsp_spectral_edge", "title": "Spectral edge frequency (e.g. SEF95)", "topics": [ "morie_dsp_spectral_edge" ] }, { "page": "morie_dsp_spectral_entropy", "title": "Spectral entropy (Shannon, base 2)", "topics": [ "morie_dsp_spectral_entropy" ] }, { "page": "morie_dsp_spectral_flatness", "title": "Spectral flatness (Wiener entropy)", "topics": [ "morie_dsp_spectral_flatness" ] }, { "page": "morie_dsp_spectral_kurtosis", "title": "Spectral kurtosis from PSD", "topics": [ "morie_dsp_spectral_kurtosis" ] }, { "page": "morie_dsp_spectral_moment", "title": "k-th spectral moment", "topics": [ "morie_dsp_spectral_moment" ] }, { "page": "morie_dsp_spectral_ratio", "title": "Spectral power ratio between two bands", "topics": [ "morie_dsp_spectral_ratio" ] }, { "page": "morie_dsp_synchronized_average", "title": "Synchronized average around trigger indices", "topics": [ "morie_dsp_synchronized_average" ] }, { "page": "morie_dsp_t_wave", "title": "T-wave detection by post-QRS argmax search", "topics": [ "morie_dsp_t_wave" ] }, { "page": "morie_dsp_teager_energy", "title": "Teager-Kaiser energy operator", "topics": [ "morie_dsp_teager_energy" ] }, { "page": "morie_dsp_template_match", "title": "Normalised template matching", "topics": [ "morie_dsp_template_match" ] }, { "page": "morie_dsp_threshold_detect", "title": "Threshold-based event detection", "topics": [ "morie_dsp_threshold_detect" ] }, { "page": "morie_dsp_turning_points", "title": "Turning-points stationarity test", "topics": [ "morie_dsp_turning_points" ] }, { "page": "morie_dsp_turns_count", "title": "Willison turns count", "topics": [ "morie_dsp_turns_count" ] }, { "page": "morie_dsp_variance_ratio", "title": "Variance ratio (x vs. y)", "topics": [ "morie_dsp_variance_ratio" ] }, { "page": "morie_dsp_waveform_length", "title": "Waveform length (total variation)", "topics": [ "morie_dsp_waveform_length" ] }, { "page": "morie_dsp_waveform_length_norm", "title": "Per-sample (normalised) waveform length", "topics": [ "morie_dsp_waveform_length_norm" ] }, { "page": "morie_dsp_wiener_filter", "title": "Wiener filter (frequency domain)", "topics": [ "morie_dsp_wiener_filter" ] }, { "page": "morie_dsp_wiener_hopf", "title": "Solve the Wiener-Hopf normal equations", "topics": [ "morie_dsp_wiener_hopf" ] }, { "page": "morie_dsp_willison_amplitude", "title": "Willison amplitude", "topics": [ "morie_dsp_willison_amplitude" ] }, { "page": "morie_dsp_window", "title": "Window function generator", "topics": [ "morie_dsp_window" ] }, { "page": "morie_dsp_zero_crossing", "title": "Zero-crossing rate", "topics": [ "morie_dsp_zero_crossing" ] }, { "page": "morie_e_value", "title": "Compute E-value for unmeasured confounding", "topics": [ "morie_e_value" ] }, { "page": "morie_effects_comparisons", "title": "Contrasts / comparisons via 'marginaleffects'", "topics": [ "morie_effects_comparisons" ] }, { "page": "morie_effects_emmeans", "title": "Estimated marginal means via 'emmeans'", "topics": [ "morie_effects_emmeans" ] }, { "page": "morie_effects_predictions", "title": "Adjusted predictions via 'marginaleffects'", "topics": [ "morie_effects_predictions" ] }, { "page": "morie_effects_slopes", "title": "Marginal slopes (partial derivatives) via 'marginaleffects'", "topics": [ "morie_effects_slopes" ] }, { "page": "morie_effects_tidy", "title": "Tidy a model with 'broom' (fallback: 'summary()' coefficients)", "topics": [ "morie_effects_tidy" ] }, { "page": "morie_eg_coint", "title": "Engle-Granger two-step cointegration test", "topics": [ "morie_eg_coint" ] }, { "page": "morie_egarch_model", "title": "EGARCH(1,1) asymmetric volatility model", "topics": [ "morie_egarch_model" ] }, { "page": "morie_ensure_extras", "title": "Ensure optional packages are installed (interactive helper)", "topics": [ "morie_ensure_extras" ] }, { "page": "morie_entheo_analyze_subject", "title": "Per-subject DMT vs PCB BOLD pipeline", "topics": [ "morie_entheo_analyze_subject" ] }, { "page": "morie_entheo_available_subjects", "title": "DMT_Imaging: list motion-survived subject IDs", "topics": [ "morie_entheo_available_subjects" ] }, { "page": "morie_entheo_clone_dmt_imaging", "title": "Clone the DMT_Imaging dataset (Timmerman et al.) into a local cache.", "topics": [ "morie_entheo_clone_dmt_imaging" ] }, { "page": "morie_entheo_dataset_overview", "title": "DMT_Imaging: dataset overview", "topics": [ "morie_entheo_dataset_overview" ] }, { "page": "morie_entheo_dynamic_functional_connectivity", "title": "Sliding-window dynamic functional connectivity (dRSFC)", "topics": [ "morie_entheo_dynamic_functional_connectivity" ] }, { "page": "morie_entheo_load_eeg_region", "title": "DMT_Imaging: load IRASA EEG regressors for one cortical region", "topics": [ "morie_entheo_load_eeg_region" ] }, { "page": "morie_entheo_load_fmri_subject", "title": "DMT_Imaging: load one subject's BOLD AAL parcellation", "topics": [ "morie_entheo_load_fmri_subject" ] }, { "page": "morie_entheo_lz_complexity", "title": "Lempel-Ziv (LZ76) complexity of a binarised signal", "topics": [ "morie_entheo_lz_complexity" ] }, { "page": "morie_entheo_spectral_band_power", "title": "EEG band-power decomposition via Welch PSD", "topics": [ "morie_entheo_spectral_band_power" ] }, { "page": "morie_estimate_aipw", "title": "Augmented IPW (AIPW) doubly-robust ATE estimator", "topics": [ "morie_estimate_aipw" ] }, { "page": "morie_estimate_atc", "title": "Estimate the Average Treatment Effect on the Controls (ATC)", "topics": [ "morie_estimate_atc" ] }, { "page": "morie_estimate_ate", "title": "Estimate the Average Treatment Effect (ATE) via Hajek IPW", "topics": [ "morie_estimate_ate" ] }, { "page": "morie_estimate_att", "title": "Estimate the Average Treatment Effect on the Treated (ATT)", "topics": [ "morie_estimate_att" ] }, { "page": "morie_estimate_cate", "title": "Estimate per-unit Conditional Average Treatment Effects (CATE)", "topics": [ "morie_estimate_cate" ] }, { "page": "morie_estimate_double_ml", "title": "Estimate ATE via Double Machine Learning (Partially Linear Regression)", "topics": [ "morie_estimate_double_ml" ] }, { "page": "morie_estimate_g_computation", "title": "G-computation (outcome regression) ATE estimator", "topics": [ "morie_estimate_g_computation" ] }, { "page": "morie_estimate_gate", "title": "Estimate Group Average Treatment Effects (GATE)", "topics": [ "morie_estimate_gate" ] }, { "page": "morie_estimate_irm", "title": "Estimate ATE via the Interactive Regression Model (IRM)", "topics": [ "morie_estimate_irm" ] }, { "page": "morie_estimate_late", "title": "Estimate the Local Average Treatment Effect (LATE) via 2SLS / Wald", "topics": [ "morie_estimate_late" ] }, { "page": "morie_estimate_propensity_scores", "title": "Estimate propensity scores via logistic regression", "topics": [ "morie_estimate_propensity_scores" ] }, { "page": "morie_ewma_volatility", "title": "EWMA volatility (RiskMetrics 1996)", "topics": [ "morie_ewma_volatility" ] }, { "page": "morie_fairness_apply_profile", "title": "Rename a city data.frame onto the canonical audit schema", "topics": [ "morie_fairness_apply_profile" ] }, { "page": "morie_fairness_average_odds_difference", "title": "Average Odds Difference (mean of TPR and FPR gaps)", "topics": [ "morie_fairness_average_odds_difference" ] }, { "page": "morie_fairness_bias_amplification", "title": "Bias Amplification Score (parity gap x Gini of group rates)", "topics": [ "morie_fairness_bias_amplification" ] }, { "page": "MORIE_FAIRNESS_CANONICAL_FIELDS", "title": "The five canonical per-area fields the audit consumes.", "topics": [ "MORIE_FAIRNESS_CANONICAL_FIELDS" ] }, { "page": "morie_fairness_city_profile", "title": "Construct a city profile (column map onto the canonical audit schema)", "topics": [ "morie_fairness_city_profile" ] }, { "page": "morie_fairness_column_map", "title": "Column map for a city profile", "topics": [ "morie_fairness_column_map" ] }, { "page": "morie_fairness_demographic_parity", "title": "Demographic Parity Gap (difference in favourable-outcome rates)", "topics": [ "morie_fairness_demographic_parity" ] }, { "page": "morie_fairness_disparate_impact", "title": "Disparate Impact Ratio (EEOC four-fifths / 80% rule)", "topics": [ "morie_fairness_disparate_impact" ] }, { "page": "morie_fairness_equalized_odds", "title": "Equalized Odds (TPR / FPR gaps across groups)", "topics": [ "morie_fairness_equalized_odds" ] }, { "page": "morie_fairness_get_city", "title": "Look up a registered city profile by case-insensitive name", "topics": [ "morie_fairness_get_city" ] }, { "page": "morie_fairness_gini", "title": "Gini coefficient (concentration of a non-negative distribution)", "topics": [ "morie_fairness_gini" ] }, { "page": "morie_fairness_list_cities", "title": "List registered city profile names", "topics": [ "morie_fairness_list_cities" ] }, { "page": "morie_fairness_noisy_or_detection", "title": "Noisy-OR patrol-detection probabilities", "topics": [ "morie_fairness_noisy_or_detection" ] }, { "page": "morie_fairness_predpol", "title": "Predictive-policing disparity audit (port of morie.fairness.predpol)", "topics": [ "morie_fairness_predpol" ] }, { "page": "morie_fairness_predpol_aggregate_areas", "title": "Aggregate per-record predictive-policing data to per-area", "topics": [ "morie_fairness_predpol_aggregate_areas" ] }, { "page": "morie_fairness_predpol_calibration_audit", "title": "Predicted-vs-realised rank audit by demographic group", "topics": [ "morie_fairness_predpol_calibration_audit" ] }, { "page": "morie_fairness_predpol_score_disparity", "title": "Descriptive score-by-group disparity", "topics": [ "morie_fairness_predpol_score_disparity" ] }, { "page": "morie_fairness_predpol_temporal_audit", "title": "Audit how disparity metrics move over time and across cities", "topics": [ "morie_fairness_predpol_temporal_audit" ] }, { "page": "morie_fairness_register_city", "title": "Register a city profile in the process-local registry", "topics": [ "morie_fairness_register_city" ] }, { "page": "morie_fairness_simulate_biased_crime_data", "title": "Synthetic predictive-policing dataset with a known disparity", "topics": [ "morie_fairness_simulate_biased_crime_data" ] }, { "page": "morie_fairness_simulation", "title": "Simulation primitives for the predictive-policing audit subsystem", "topics": [ "morie_fairness_simulation" ] }, { "page": "morie_fairness_xai", "title": "Model-agnostic explainability (XAI) for bias discovery", "topics": [ "morie_fairness_xai" ] }, { "page": "morie_fairness_xai_ale", "title": "First-order Accumulated Local Effects (Apley & Zhu)", "topics": [ "morie_fairness_xai_ale" ] }, { "page": "morie_fairness_xai_ceteris_paribus", "title": "Ceteris-paribus profile for one instance", "topics": [ "morie_fairness_xai_ceteris_paribus" ] }, { "page": "morie_fairness_xai_partial_dependence", "title": "Partial dependence on one feature (Friedman)", "topics": [ "morie_fairness_xai_partial_dependence" ] }, { "page": "morie_fairness_xai_permutation_importance", "title": "Permutation feature importance (model-agnostic)", "topics": [ "morie_fairness_xai_permutation_importance" ] }, { "page": "morie_fairness_xai_shap_values", "title": "Shapley feature attributions for one instance (sampling estimator)", "topics": [ "morie_fairness_xai_shap_values" ] }, { "page": "morie_fast_available", "title": "Is the R-side JIT acceleration active?", "topics": [ "morie_fast_available" ] }, { "page": "morie_fdr_qvalues", "title": "FDR / q-values / tail-area p-values via 'fdrtool'", "topics": [ "morie_fdr_qvalues" ] }, { "page": "morie_fetch", "title": "Fetch a dataset from any URL, with automatic format detection", "topics": [ "morie_fetch" ] }, { "page": "morie_fetch_arcgis", "title": "Query an ArcGIS FeatureServer / MapServer layer", "topics": [ "morie_fetch_arcgis" ] }, { "page": "morie_fetch_ckan", "title": "Fetch data from the CKAN API and cache it", "topics": [ "morie_fetch_ckan" ] }, { "page": "morie_fetch_siu", "title": "Fetch the Ontario SIU corpus into a 64-column SIU.csv", "topics": [ "morie_fetch_siu" ] }, { "page": "morie_fetch_tps", "title": "Fetch a TPS category from the Toronto Police ArcGIS REST endpoint", "topics": [ "morie_fetch_tps" ] }, { "page": "morie_fisher_exact_test", "title": "Fisher's exact test for 2x2 tables", "topics": [ "morie_fisher_exact_test" ] }, { "page": "morie_garch_fit", "title": "Fit a GARCH(1,1) model to a return series", "topics": [ "morie_garch_fit" ] }, { "page": "morie_gblup_full", "title": "GBLUP - full mixed-model implementation", "topics": [ "morie_gblup_full" ] }, { "page": "morie_generate_ar_coefficients", "title": "Generate a stationarity-preserving AR coefficient matrix", "topics": [ "morie_generate_ar_coefficients" ] }, { "page": "morie_generate_synthetic_data", "title": "Generate synthetic epidemiology-style tabular data", "topics": [ "morie_generate_synthetic_data" ] }, { "page": "morie_generate_var_coefficients", "title": "Generate a VAR(L) coefficient array as a 3-d list", "topics": [ "morie_generate_var_coefficients" ] }, { "page": "morie_genomic_cross_validation", "title": "K-fold cross-validation for genomic-prediction accuracy", "topics": [ "morie_genomic_cross_validation" ] }, { "page": "morie_geostat_krige", "title": "Kriging interpolation via 'gstat'", "topics": [ "morie_geostat_krige" ] }, { "page": "morie_geostat_variogram", "title": "Empirical variogram via 'gstat'", "topics": [ "morie_geostat_variogram" ] }, { "page": "morie_ghosal_adaptation", "title": "Adaptive contraction rates over a smoothness grid.", "topics": [ "morie_ghosal_adaptation" ] }, { "page": "morie_ghosal_bernstein_von_mises", "title": "BvM diagnostic for the mean functional under a DP prior.", "topics": [ "morie_ghosal_bernstein_von_mises" ] }, { "page": "morie_ghosal_contraction_rate", "title": "Minimax posterior-contraction rate", "topics": [ "morie_ghosal_contraction_rate" ] }, { "page": "morie_ghosal_dirichlet_posterior", "title": "Dirichlet-process posterior (conjugate update)", "topics": [ "morie_ghosal_dirichlet_posterior" ] }, { "page": "morie_ghosal_dpmixture_density", "title": "DP mixture density estimate (Neal 2000 algorithm 3)", "topics": [ "morie_ghosal_dpmixture_density" ] }, { "page": "morie_ghosal_empirical_bayes", "title": "Empirical-Bayes alpha MLE for a DP, given the observed K_n.", "topics": [ "morie_ghosal_empirical_bayes" ] }, { "page": "morie_ghosal_gp_matern", "title": "GP posterior mean with Matern kernel.", "topics": [ "morie_ghosal_gp_matern" ] }, { "page": "morie_ghosal_gp_squared_exponential", "title": "GP posterior mean with squared-exponential kernel.", "topics": [ "morie_ghosal_gp_squared_exponential" ] }, { "page": "morie_ghosal_hierarchical_bayes", "title": "Escobar-West augmentation for alpha given K_n with a Gamma(a, b) hyperprior.", "topics": [ "morie_ghosal_hierarchical_bayes" ] }, { "page": "morie_ghosal_log_density", "title": "Log-spline density estimator (Stone 1990, Ghosal Ch 8).", "topics": [ "morie_ghosal_log_density" ] }, { "page": "morie_ghosal_moment_matching", "title": "Posterior mean / variance of G(A) for DP(alpha, G0) and A = (A_lower, A_upper].", "topics": [ "morie_ghosal_moment_matching" ] }, { "page": "morie_ghosal_neutral_right", "title": "Neutral-to-the-right posterior survival (Doksum 1974).", "topics": [ "morie_ghosal_neutral_right" ] }, { "page": "morie_ghosal_np_classification", "title": "Probit-GP classifier (Laplace approximation).", "topics": [ "morie_ghosal_np_classification" ] }, { "page": "morie_ghosal_np_regression", "title": "GP nonparametric regression", "topics": [ "morie_ghosal_np_regression" ] }, { "page": "morie_ghosal_np_testing", "title": "Polya-tree Bayes factor for H0: F = N(loc, scale^2).", "topics": [ "morie_ghosal_np_testing" ] }, { "page": "morie_ghosal_posterior_consistency", "title": "Schwartz posterior-consistency diagnostic (Bayesian bootstrap).", "topics": [ "morie_ghosal_posterior_consistency" ] }, { "page": "morie_ghosal_sieve_prior", "title": "Bernstein-polynomial sieve density estimator (Petrone 1999).", "topics": [ "morie_ghosal_sieve_prior" ] }, { "page": "morie_ghosal_stick_breaking_trunc", "title": "Truncated stick-breaking representation of DP(alpha, G0).", "topics": [ "morie_ghosal_stick_breaking_trunc" ] }, { "page": "morie_ghosal_survival_beta_process", "title": "Beta-process posterior survival (Hjort 1990).", "topics": [ "morie_ghosal_survival_beta_process" ] }, { "page": "morie_ghosal_wavelet_prior", "title": "Haar-wavelet spike-and-slab BayesThresh estimator (Abramovich 1998).", "topics": [ "morie_ghosal_wavelet_prior" ] }, { "page": "morie_gpl_compatible_licenses", "title": "Vector of SPDX identifiers recognised as GPL-compatible", "topics": [ "morie_gpl_compatible_licenses" ] }, { "page": "morie_gradient_boosting_ensemble", "title": "Gradient boosting ensemble (R parity)", "topics": [ "morie_gradient_boosting_ensemble" ] }, { "page": "morie_gradient_boosting_genomic", "title": "Gradient-boosting genomic predictor (Friedman 2001)", "topics": [ "morie_gradient_boosting_genomic" ] }, { "page": "morie_gradient_descent_vanilla", "title": "Vanilla batch gradient descent for OLS (R parity)", "topics": [ "morie_gradient_descent_vanilla" ] }, { "page": "morie_grid_search_cv", "title": "Grid search with cross-validation (R parity)", "topics": [ "morie_grid_search_cv" ] }, { "page": "morie_grm_vanraden", "title": "VanRaden Genomic Relationship Matrix", "topics": [ "morie_grm_vanraden" ] }, { "page": "morie_gxe_interaction_model", "title": "Two-way GxE ANOVA with EMS variance components", "topics": [ "morie_gxe_interaction_model" ] }, { "page": "morie_hawkes_fit", "title": "Fit a Hawkes (self-exciting point process) model by maximum likelihood", "topics": [ "morie_hawkes_fit" ] }, { "page": "morie_hurst_r", "title": "Hurst exponent via rescaled-range (R/S) analysis", "topics": [ "morie_hurst_r" ] }, { "page": "morie_infer_measurement_level", "title": "Infer the measurement level of a vector", "topics": [ "morie_infer_measurement_level" ] }, { "page": "morie_ingest_bigquery_build_sql", "title": "Build a parameter-safe BigQuery SELECT", "topics": [ "morie_ingest_bigquery_build_sql" ] }, { "page": "morie_ingest_bigquery_query", "title": "Execute a BigQuery SQL query and return a data.frame", "topics": [ "morie_ingest_bigquery_query" ] }, { "page": "morie_ingest_bigquery_table", "title": "Pull a BigQuery table (or filtered slice) into a data.frame", "topics": [ "morie_ingest_bigquery_table" ] }, { "page": "morie_ingest_chicago_crime", "title": "Pull the City of Chicago \"Crimes - 2001 to Present\" feed", "topics": [ "morie_ingest_chicago_crime" ] }, { "page": "morie_ingest_chicago_crime_bigquery", "title": "BigQuery mirror of the Chicago crime feed", "topics": [ "morie_ingest_chicago_crime_bigquery" ] }, { "page": "morie_ingest_chicago_resources", "title": "Built-in Chicago / Socrata resource registry", "topics": [ "morie_ingest_chicago_resources" ] }, { "page": "morie_ingest_chicago_socrata", "title": "Fetch every row from a Socrata SoDA JSON endpoint", "topics": [ "morie_ingest_chicago_socrata" ] }, { "page": "morie_ingest_cihi_xlsx", "title": "Download a CIHI indicator .xlsx data table", "topics": [ "morie_ingest_cihi_xlsx" ] }, { "page": "morie_ingest_ckan_fetch_package_csvs", "title": "Fetch every CSV / TSV resource in a CKAN package", "topics": [ "morie_ingest_ckan_fetch_package_csvs" ] }, { "page": "morie_ingest_ckan_package_search", "title": "Search a CKAN portal for packages (raw)", "topics": [ "morie_ingest_ckan_package_search" ] }, { "page": "morie_ingest_ckan_package_show", "title": "Fetch one CKAN package's metadata", "topics": [ "morie_ingest_ckan_package_show" ] }, { "page": "morie_ingest_ckan_read_resource", "title": "Download a CKAN resource as a data.frame", "topics": [ "morie_ingest_ckan_read_resource" ] }, { "page": "morie_ingest_ckan_resource_show", "title": "Fetch one CKAN resource's metadata", "topics": [ "morie_ingest_ckan_resource_show" ] }, { "page": "morie_ingest_ckan_search_packages", "title": "Search a CKAN portal and return a flat metadata data.frame", "topics": [ "morie_ingest_ckan_search_packages" ] }, { "page": "morie_ingest_forensics_namus_missing", "title": "Pull NamUs missing-persons case metadata", "topics": [ "morie_ingest_forensics_namus_missing" ] }, { "page": "morie_ingest_forensics_nibrs", "title": "Pull FBI NIBRS offence-event records via Crime Data Explorer", "topics": [ "morie_ingest_forensics_nibrs" ] }, { "page": "morie_ingest_forensics_nist_rds", "title": "Pull NIST Reference Datasets (RDS) catalog metadata", "topics": [ "morie_ingest_forensics_nist_rds" ] }, { "page": "morie_ingest_statcan_cansim", "title": "Fetch a Statistics Canada NDM / cansim table", "topics": [ "morie_ingest_statcan_cansim" ] }, { "page": "morie_ingest_statcan_csv", "title": "Download a StatCan PUMF / CSV product", "topics": [ "morie_ingest_statcan_csv" ] }, { "page": "morie_ingest_tps_feature_layer", "title": "Fetch every feature from a TPS ArcGIS FeatureServer layer", "topics": [ "morie_ingest_tps_feature_layer" ] }, { "page": "morie_ingest_tps_fetch", "title": "Fetch a TPS open-data layer by short name", "topics": [ "morie_ingest_tps_fetch" ] }, { "page": "morie_ingest_tps_layers", "title": "Built-in TPS open-data layer registry", "topics": [ "morie_ingest_tps_layers" ] }, { "page": "morie_inspect_output", "title": "Inspect a serialised analysis output (JSON, CSV, or RDS)", "topics": [ "morie_inspect_output" ] }, { "page": "morie_install_extras", "title": "Install morie's optional dependencies (interactive helper)", "topics": [ "morie_install_extras" ] }, { "page": "morie_is_over_legal_limit", "title": "Test whether an eBAC exceeds a legal driving limit", "topics": [ "morie_is_over_legal_limit" ] }, { "page": "morie_iv_anderson_rubin", "title": "Anderson-Rubin (AR) weak-IV-robust test", "topics": [ "morie_iv_anderson_rubin" ] }, { "page": "morie_iv_anderson_rubin_ci", "title": "Grid-based Anderson-Rubin confidence interval for a single endogenous variable.", "topics": [ "morie_iv_anderson_rubin_ci" ] }, { "page": "morie_iv_conditional_lr", "title": "Conditional likelihood-ratio (CLR) test of Moreira (2003)", "topics": [ "morie_iv_conditional_lr" ] }, { "page": "morie_iv_control_function", "title": "Control-function (residual augmentation) IV", "topics": [ "morie_iv_control_function" ] }, { "page": "morie_iv_cragg_donald", "title": "Cragg-Donald weak-instrument F statistic", "topics": [ "morie_iv_cragg_donald" ] }, { "page": "morie_iv_cue_gmm", "title": "Continuously-Updated GMM (CUE-GMM)", "topics": [ "morie_iv_cue_gmm" ] }, { "page": "morie_iv_diagnostics", "title": "Composite IV diagnostics", "topics": [ "morie_iv_diagnostics" ] }, { "page": "morie_iv_durbin_wu_hausman", "title": "Durbin-Wu-Hausman test of endogeneity", "topics": [ "morie_iv_durbin_wu_hausman" ] }, { "page": "morie_iv_first_stage_diagnostics", "title": "First-stage F-statistics and partial R^2", "topics": [ "morie_iv_first_stage_diagnostics" ] }, { "page": "morie_iv_gmm", "title": "Generalised Method of Moments (GMM) IV", "topics": [ "morie_iv_gmm" ] }, { "page": "morie_iv_hansen_j", "title": "Hansen J test of overidentifying restrictions (robust)", "topics": [ "morie_iv_hansen_j" ] }, { "page": "morie_iv_hausman", "title": "Hausman test: OLS vs 2SLS", "topics": [ "morie_iv_hausman" ] }, { "page": "morie_iv_jive", "title": "Jackknife IV (JIVE; Angrist, Imbens & Krueger 1999)", "topics": [ "morie_iv_jive" ] }, { "page": "morie_iv_kleibergen_paap", "title": "Kleibergen-Paap rank statistic", "topics": [ "morie_iv_kleibergen_paap" ] }, { "page": "morie_iv_liml", "title": "Limited-Information Maximum Likelihood (LIML)", "topics": [ "morie_iv_liml" ] }, { "page": "morie_iv_panel", "title": "Panel IV with unit (and optional time) fixed effects via within-transform", "topics": [ "morie_iv_panel" ] }, { "page": "morie_iv_probit", "title": "IV Probit (Rivers-Vuong control function)", "topics": [ "morie_iv_probit" ] }, { "page": "morie_iv_residual_analysis", "title": "IV residual analysis", "topics": [ "morie_iv_residual_analysis" ] }, { "page": "morie_iv_sargan", "title": "Sargan test of overidentifying restrictions (homoskedastic)", "topics": [ "morie_iv_sargan" ] }, { "page": "morie_iv_split_sample", "title": "Split-sample IV", "topics": [ "morie_iv_split_sample" ] }, { "page": "morie_iv_stock_yogo", "title": "Stock-Yogo critical values", "topics": [ "morie_iv_stock_yogo" ] }, { "page": "morie_iv_tsls", "title": "Two-Stage Least Squares (2SLS)", "topics": [ "morie_iv_tsls" ] }, { "page": "morie_iv_wald", "title": "Wald (single-instrument) estimator", "topics": [ "morie_iv_wald" ] }, { "page": "morie_jackknife_estimate", "title": "Delete-1 jackknife variance estimate", "topics": [ "morie_jackknife_estimate" ] }, { "page": "morie_johansen_cointegration", "title": "Johansen trace test for cointegration", "topics": [ "morie_johansen_cointegration" ] }, { "page": "morie_kalman_filter", "title": "Kalman filter predict-update for a linear-Gaussian state-space model", "topics": [ "morie_kalman_filter" ] }, { "page": "morie_kendall_tau", "title": "Kendall's tau-b", "topics": [ "morie_kendall_tau" ] }, { "page": "morie_kendall_tau_partial", "title": "Kendall partial-tau correlation (Gibbons Ch 12.6)", "topics": [ "morie_kendall_tau_partial" ] }, { "page": "morie_kernel_pca", "title": "Kernel principal components analysis via 'kernlab'", "topics": [ "morie_kernel_pca" ] }, { "page": "morie_kmeans_clustering", "title": "K-means clustering (R parity)", "topics": [ "morie_kmeans_clustering" ] }, { "page": "morie_kruskal_wallis_test", "title": "Kruskal-Wallis non-parametric ANOVA", "topics": [ "morie_kruskal_wallis_test" ] }, { "page": "morie_laniyonu_actuarial_risk_disparity", "title": "Replication of O'Connell & Laniyonu (2025) — CSC actuarial-risk disparity", "topics": [ "morie_laniyonu_actuarial_risk_disparity" ] }, { "page": "morie_laniyonu_gentrification_policing", "title": "Replication of Laniyonu (2018) — Coffee Shops and Street Stops", "topics": [ "morie_laniyonu_gentrification_policing" ] }, { "page": "morie_laniyonu_smi_force_disparity", "title": "Replication of Laniyonu & Goff (2021) — Police force vs SMI disparity", "topics": [ "morie_laniyonu_smi_force_disparity" ] }, { "page": "morie_lcmm_latent_class", "title": "Latent-class mixed models via 'lcmm'", "topics": [ "morie_lcmm_latent_class" ] }, { "page": "morie_learning_curve", "title": "Learning curve - train / val MSE vs training-set size (R parity)", "topics": [ "morie_learning_curve" ] }, { "page": "morie_levene_test", "title": "Levene test for equality of variances", "topics": [ "morie_levene_test" ] }, { "page": "morie_license_metadata", "title": "morie's SPDX-style licence metadata", "topics": [ "morie_license_metadata" ] }, { "page": "morie_linear_regression_ols", "title": "Ordinary least squares closed-form solution (R parity)", "topics": [ "morie_linear_regression_ols" ] }, { "page": "morie_list_datasets", "title": "List all datasets with cache status", "topics": [ "morie_list_datasets" ] }, { "page": "morie_list_morie_modules", "title": "List implemented MORIE CPADS modules", "topics": [ "morie_list_morie_modules" ] }, { "page": "morie_llm_agent_available", "title": "Return TRUE when at least one live LLM provider is available", "topics": [ "morie_llm_agent_available" ] }, { "page": "morie_llm_ask", "title": "Send a prompt to the best available LLM provider", "topics": [ "morie_llm_ask" ] }, { "page": "morie_llm_ask_multi", "title": "Ask the best available LLM provider, accepting a multi-turn messages list", "topics": [ "morie_llm_ask_multi" ] }, { "page": "morie_llm_detect_provider", "title": "Detect the active LLM provider", "topics": [ "morie_llm_detect_provider" ] }, { "page": "morie_llm_list_freeapi_models", "title": "List vendored OllamaFreeAPI model catalogue", "topics": [ "morie_llm_list_freeapi_models" ] }, { "page": "morie_llm_probe_freeapi", "title": "Probe an OllamaFreeAPI community server", "topics": [ "morie_llm_probe_freeapi" ] }, { "page": "morie_llm_probe_ollama", "title": "Probe a local Ollama instance", "topics": [ "morie_llm_probe_ollama" ] }, { "page": "morie_llm_request_completion", "title": "POST a chat-completion request to an OpenAI-compatible endpoint", "topics": [ "morie_llm_request_completion" ] }, { "page": "morie_load_cpads", "title": "Load CPADS data: local files -> cache -> CKAN API", "topics": [ "morie_load_cpads" ] }, { "page": "morie_load_cpads_data", "title": "Load the real CPADS CSV from this repository", "topics": [ "morie_load_cpads_data" ] }, { "page": "morie_load_dataset", "title": "Load a dataset by catalog key", "topics": [ "morie_load_dataset" ] }, { "page": "morie_locfdr_estimate", "title": "Local FDR estimation via 'locfdr'", "topics": [ "morie_locfdr_estimate" ] }, { "page": "morie_mann_whitney_test", "title": "Mann-Whitney U test (Wilcoxon rank-sum)", "topics": [ "morie_mann_whitney_test" ] }, { "page": "morie_marker_variance", "title": "Marker variance-component estimation", "topics": [ "morie_marker_variance" ] }, { "page": "morie_matching_abadie_imbens_se", "title": "Abadie-Imbens standard error for matching estimators", "topics": [ "morie_matching_abadie_imbens_se" ] }, { "page": "morie_matching_atc_matched", "title": "ATC from a matched sample", "topics": [ "morie_matching_atc_matched" ] }, { "page": "morie_matching_ate_matched", "title": "ATE from a matched / weighted sample", "topics": [ "morie_matching_ate_matched" ] }, { "page": "morie_matching_att_matched", "title": "ATT from a matched sample", "topics": [ "morie_matching_att_matched" ] }, { "page": "morie_matching_balance", "title": "Balance diagnostics for matched / weighted samples", "topics": [ "morie_matching_balance" ] }, { "page": "morie_matching_balance_table", "title": "Publication-ready balance table", "topics": [ "morie_matching_balance_table" ] }, { "page": "morie_matching_cardinality", "title": "Cardinality matching", "topics": [ "morie_matching_cardinality" ] }, { "page": "morie_matching_cem", "title": "Coarsened Exact Matching (CEM)", "topics": [ "morie_matching_cem" ] }, { "page": "morie_matching_common_support", "title": "Restrict a sample to the region of common support", "topics": [ "morie_matching_common_support" ] }, { "page": "morie_matching_doubly_robust", "title": "Doubly-robust ATT combining matching and regression", "topics": [ "morie_matching_doubly_robust" ] }, { "page": "morie_matching_entropy_balance", "title": "Entropy balancing weights (Hainmueller, 2012)", "topics": [ "morie_matching_entropy_balance" ] }, { "page": "morie_matching_estimate_propensity", "title": "Estimate propensity scores", "topics": [ "morie_matching_estimate_propensity" ] }, { "page": "morie_matching_exact", "title": "Exact matching on discrete covariates", "topics": [ "morie_matching_exact" ] }, { "page": "morie_matching_full", "title": "Full matching via subclassification", "topics": [ "morie_matching_full" ] }, { "page": "morie_matching_genetic", "title": "Genetic matching (Diamond & Sekhon, 2013)", "topics": [ "morie_matching_genetic" ] }, { "page": "morie_matching_longitudinal", "title": "Longitudinal matching for panel data", "topics": [ "morie_matching_longitudinal" ] }, { "page": "morie_matching_love_plot_data", "title": "Love-plot data: pre- vs post-matching balance", "topics": [ "morie_matching_love_plot_data" ] }, { "page": "morie_matching_mahalanobis", "title": "Mahalanobis distance matching", "topics": [ "morie_matching_mahalanobis" ] }, { "page": "morie_matching_multi_treatment", "title": "Matching with multiple (> 2) treatment groups", "topics": [ "morie_matching_multi_treatment" ] }, { "page": "morie_matching_nearest_neighbor", "title": "Nearest-neighbour propensity-score matching", "topics": [ "morie_matching_nearest_neighbor" ] }, { "page": "morie_matching_optimal_pair", "title": "Optimal pair matching", "topics": [ "morie_matching_optimal_pair" ] }, { "page": "morie_matching_overlap", "title": "Propensity-score overlap diagnostics", "topics": [ "morie_matching_overlap" ] }, { "page": "morie_matching_quality", "title": "Comprehensive matching-quality assessment", "topics": [ "morie_matching_quality" ] }, { "page": "morie_matching_rosenbaum_bounds", "title": "Rosenbaum bounds for hidden bias", "topics": [ "morie_matching_rosenbaum_bounds" ] }, { "page": "morie_matching_subclassify", "title": "Subclassification (stratification) on the propensity score", "topics": [ "morie_matching_subclassify" ] }, { "page": "morie_matching_trim_propensity", "title": "Trim propensity scores to a fixed range", "topics": [ "morie_matching_trim_propensity" ] }, { "page": "morie_matching_variable_ratio", "title": "Variable-ratio matching on propensity score", "topics": [ "morie_matching_variable_ratio" ] }, { "page": "morie_meta_rma", "title": "Random- / fixed-effects meta-analysis via 'metafor'", "topics": [ "morie_meta_rma" ] }, { "page": "morie_midas_regression", "title": "MIDAS regression with Beta-polynomial weights", "topics": [ "morie_midas_regression" ] }, { "page": "morie_mini_batch_gradient", "title": "Mini-batch stochastic gradient descent for OLS (R parity)", "topics": [ "morie_mini_batch_gradient" ] }, { "page": "morie_ml_apply_smote", "title": "Apply SMOTE oversampling to balance a binary outcome", "topics": [ "morie_ml_apply_smote" ] }, { "page": "morie_ml_eval_robustness", "title": "Evaluate Random Forest robustness", "topics": [ "morie_ml_eval_robustness" ] }, { "page": "morie_multi_trait_gblup", "title": "Multi-trait GBLUP via vec-stacked mixed-model equations", "topics": [ "morie_multi_trait_gblup" ] }, { "page": "morie_multiple_testing", "title": "Multiple testing correction and multiplicity-adjusted inference", "topics": [ "morie_multiple_testing" ] }, { "page": "morie_mvn_with_covariance", "title": "Draw multivariate normal samples under a structured covariance", "topics": [ "morie_mvn_with_covariance" ] }, { "page": "morie_mvnorm_pmv", "title": "Multivariate normal rectangle probability via 'mvtnorm'", "topics": [ "morie_mvnorm_pmv" ] }, { "page": "morie_mvnorm_sample", "title": "Sample from the multivariate normal via 'mvtnorm'", "topics": [ "morie_mvnorm_sample" ] }, { "page": "morie_nbeats_basis", "title": "N-BEATS-style polynomial + Fourier basis-expansion forecasting", "topics": [ "morie_nbeats_basis" ] }, { "page": "morie_np_kernel_reg", "title": "Nonparametric kernel regression via 'np'", "topics": [ "morie_np_kernel_reg" ] }, { "page": "morie_nyc_nypd_socrata_cap_note", "title": "Socrata default-API-cap note + pagination wiring", "topics": [ "morie_nyc_nypd_socrata_cap_note" ] }, { "page": "morie_odds_ratio_ci", "title": "Odds ratio and 95% CI from a 2x2 contingency table", "topics": [ "morie_odds_ratio_ci" ] }, { "page": "morie_omega_squared", "title": "Omega-squared (less biased than eta-squared)", "topics": [ "morie_omega_squared" ] }, { "page": "morie_one_sample_coverage", "title": "One-sample coverage probability (Gibbons Ch 2.11.1)", "topics": [ "morie_one_sample_coverage" ] }, { "page": "morie_one_sample_t_test", "title": "One-sample t-test", "topics": [ "morie_one_sample_t_test" ] }, { "page": "morie_ordered_alternatives_test", "title": "Jonckheere-Terpstra ordered-alternatives test (Gibbons Ch 10.6)", "topics": [ "morie_ordered_alternatives_test" ] }, { "page": "morie_ordered_categories", "title": "Linear-by-linear association test for ordered categories (Gibbons Ch 14.6.1)", "topics": [ "morie_ordered_categories" ] }, { "page": "morie_otis_aipw_ate", "title": "Doubly-robust (AIPW) ATE on OTIS data via cross-fitted nuisances.", "topics": [ "morie_otis_aipw_ate" ] }, { "page": "morie_otis_aipw_superlearner", "title": "SuperLearner-stacked AIPW (not yet ported).", "topics": [ "morie_otis_aipw_superlearner" ] }, { "page": "morie_otis_all_analyses", "title": "Run the full OTIS analysis bundle", "topics": [ "morie_otis_all_analyses" ] }, { "page": "morie_otis_all_analyze", "title": "Comprehensive per-dataset analyses for ALL 28 OTIS public-release files", "topics": [ "morie_otis_all_analyze" ] }, { "page": "morie_otis_analyze_a01", "title": "OTIS a01 high-level causal analysis (MatchIt + IRM-DML).", "topics": [ "morie_otis_analyze_a01" ] }, { "page": "morie_otis_analyze_a01_ruhela_alt_age", "title": "a01 alt-T Ruhela: Age 50+ -> vm count.", "topics": [ "morie_otis_analyze_a01_mrm_alt_age", "morie_otis_analyze_a01_ruhela_alt_age" ] }, { "page": "morie_otis_analyze_a01_ruhela_alt_gender", "title": "a01 alt-T Ruhela: Female -> vm count.", "topics": [ "morie_otis_analyze_a01_mrm_alt_gender", "morie_otis_analyze_a01_ruhela_alt_gender" ] }, { "page": "morie_otis_analyze_a01_ruhela_alt_toronto", "title": "a01 alt-T Ruhela: Toronto region -> vm count.", "topics": [ "morie_otis_analyze_a01_mrm_alt_toronto", "morie_otis_analyze_a01_ruhela_alt_toronto" ] }, { "page": "morie_otis_analyze_a01_ruhela_formulations", "title": "OTIS a01 Ruhela formulations (full DLRM).", "topics": [ "morie_otis_analyze_a01_dlrm", "morie_otis_analyze_a01_mrm", "morie_otis_analyze_a01_ruhela_formulations" ] }, { "page": "morie_otis_analyze_a01_ruhela_per_year", "title": "Per-year full-DLRM on a01 canonical formulation.", "topics": [ "morie_otis_analyze_a01_mrm_per_year", "morie_otis_analyze_a01_ruhela_per_year" ] }, { "page": "morie_otis_analyze_a01_ruhela_subgroup_female", "title": "a01 subgroup Ruhela: Female-only cell frame.", "topics": [ "morie_otis_analyze_a01_mrm_subgroup_female", "morie_otis_analyze_a01_ruhela_subgroup_female" ] }, { "page": "morie_otis_analyze_a01_ruhela_subgroup_male", "title": "a01 subgroup Ruhela: Male-only cell frame.", "topics": [ "morie_otis_analyze_a01_mrm_subgroup_male", "morie_otis_analyze_a01_ruhela_subgroup_male" ] }, { "page": "morie_otis_analyze_a01_with_csi_context", "title": "OTIS a01 causal pipeline + Toronto Crime Severity Index context.", "topics": [ "morie_otis_analyze_a01_with_csi_context" ] }, { "page": "morie_otis_analyze_all", "title": "Run every OTIS analyzer against a named list of datasets", "topics": [ "morie_otis_analyze_all" ] }, { "page": "morie_otis_analyze_b01", "title": "Person-level segregation-placement analysis (b01)", "topics": [ "morie_otis_analyze_b01" ] }, { "page": "morie_otis_analyze_b01_ruhela_alt_age", "title": "b01 alt-T Ruhela: Age 50+ -> vm count.", "topics": [ "morie_otis_analyze_b01_mrm_alt_age", "morie_otis_analyze_b01_ruhela_alt_age" ] }, { "page": "morie_otis_analyze_b01_ruhela_alt_gender", "title": "b01 alt-T Ruhela: Female -> vm count.", "topics": [ "morie_otis_analyze_b01_mrm_alt_gender", "morie_otis_analyze_b01_ruhela_alt_gender" ] }, { "page": "morie_otis_analyze_b01_ruhela_alt_toronto", "title": "b01 alt-T Ruhela: Toronto region -> vm count.", "topics": [ "morie_otis_analyze_b01_mrm_alt_toronto", "morie_otis_analyze_b01_ruhela_alt_toronto" ] }, { "page": "morie_otis_analyze_b01_ruhela_formulations", "title": "OTIS b01 Ruhela formulations (full DLRM).", "topics": [ "morie_otis_analyze_b01_dlrm", "morie_otis_analyze_b01_mrm", "morie_otis_analyze_b01_ruhela_formulations" ] }, { "page": "morie_otis_analyze_b01_ruhela_per_year", "title": "Per-year full-DLRM on b01 canonical formulation.", "topics": [ "morie_otis_analyze_b01_mrm_per_year", "morie_otis_analyze_b01_ruhela_per_year" ] }, { "page": "morie_otis_analyze_b01_ruhela_subgroup_female", "title": "b01 subgroup Ruhela: Female-only cell frame.", "topics": [ "morie_otis_analyze_b01_mrm_subgroup_female", "morie_otis_analyze_b01_ruhela_subgroup_female" ] }, { "page": "morie_otis_analyze_b01_ruhela_subgroup_male", "title": "b01 subgroup Ruhela: Male-only cell frame.", "topics": [ "morie_otis_analyze_b01_mrm_subgroup_male", "morie_otis_analyze_b01_ruhela_subgroup_male" ] }, { "page": "morie_otis_analyze_b02", "title": "Aggregate segregation days per person per year (b02)", "topics": [ "morie_otis_analyze_b02" ] }, { "page": "morie_otis_analyze_b02_ruhela_alt_age", "title": "b02 alt-T Ruhela: Age 50+ -> total seg days.", "topics": [ "morie_otis_analyze_b02_mrm_alt_age", "morie_otis_analyze_b02_ruhela_alt_age" ] }, { "page": "morie_otis_analyze_b02_ruhela_alt_region", "title": "b02 alt-T Ruhela: Toronto region -> total seg days.", "topics": [ "morie_otis_analyze_b02_mrm_alt_region", "morie_otis_analyze_b02_ruhela_alt_region" ] }, { "page": "morie_otis_analyze_b02_ruhela_formulations", "title": "OTIS b02 Ruhela formulations: T=Female -> seg-day count.", "topics": [ "morie_otis_analyze_b02_dlrm", "morie_otis_analyze_b02_mrm", "morie_otis_analyze_b02_ruhela_formulations" ] }, { "page": "morie_otis_analyze_b03", "title": "Segregation placements by alert x institution (b03)", "topics": [ "morie_otis_analyze_b03" ] }, { "page": "morie_otis_analyze_b03_ruhela_aggregate", "title": "b03 aggregate Ruhela: Alert presence -> seg placements.", "topics": [ "morie_otis_analyze_b03_mrm_aggregate", "morie_otis_analyze_b03_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_b04", "title": "Placement durations by region & gender (b04)", "topics": [ "morie_otis_analyze_b04" ] }, { "page": "morie_otis_analyze_b04_ruhela_aggregate", "title": "b04 aggregate Ruhela: Female -> median seg duration.", "topics": [ "morie_otis_analyze_b04_mrm_aggregate", "morie_otis_analyze_b04_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_b05", "title": "Distribution of placements by binned duration (b05)", "topics": [ "morie_otis_analyze_b05" ] }, { "page": "morie_otis_analyze_b05_mandela_classification", "title": "Mandela-RF on b05 - per-placement Mandela classification by year.", "topics": [ "morie_otis_analyze_b05_mandela_classification" ] }, { "page": "morie_otis_analyze_b05_ruhela_aggregate", "title": "b05 aggregate Ruhela: schema-no-demographic guard.", "topics": [ "morie_otis_analyze_b05_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_b06", "title": "Reasons for placement x institution x gender (b06)", "topics": [ "morie_otis_analyze_b06" ] }, { "page": "morie_otis_analyze_b06_ruhela_aggregate", "title": "b06 aggregate Ruhela: Disciplinary reason -> seg placements.", "topics": [ "morie_otis_analyze_b06_mrm_aggregate", "morie_otis_analyze_b06_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_b07", "title": "Alerts x gender (b07)", "topics": [ "morie_otis_analyze_b07" ] }, { "page": "morie_otis_analyze_b07_ruhela_aggregate", "title": "b07 aggregate Ruhela (pivot to long): With-alert -> seg placements.", "topics": [ "morie_otis_analyze_b07_mrm_aggregate", "morie_otis_analyze_b07_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_b08", "title": "Durations by institution & gender (b08)", "topics": [ "morie_otis_analyze_b08" ] }, { "page": "morie_otis_analyze_b08_ruhela_aggregate", "title": "b08 aggregate Ruhela: Female -> median seg duration (institution-clustered).", "topics": [ "morie_otis_analyze_b08_mrm_aggregate", "morie_otis_analyze_b08_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_b09", "title": "Individuals by number of placements x gender (b09)", "topics": [ "morie_otis_analyze_b09" ] }, { "page": "morie_otis_analyze_b09_ruhela_aggregate", "title": "b09 aggregate Ruhela: Female -> individuals in segregation.", "topics": [ "morie_otis_analyze_b09_mrm_aggregate", "morie_otis_analyze_b09_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c_chi2", "title": "MRM chi-square family on c-series.", "topics": [ "morie_otis_analyze_c_chi2" ] }, { "page": "morie_otis_analyze_c01", "title": "Total individuals x custody/RC/seg x gender (c01)", "topics": [ "morie_otis_analyze_c01" ] }, { "page": "morie_otis_analyze_c01_ruhela_aggregate", "title": "c01 aggregate Ruhela: Female -> RC count.", "topics": [ "morie_otis_analyze_c01_mrm_aggregate", "morie_otis_analyze_c01_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c01_ruhela_aggregate_region_cluster", "title": "c01 region-cluster variant (year-clustered GEE).", "topics": [ "morie_otis_analyze_c01_mrm_aggregate_region_cluster", "morie_otis_analyze_c01_ruhela_aggregate_region_cluster" ] }, { "page": "morie_otis_analyze_c02", "title": "Individuals in RC/seg by institution (c02)", "topics": [ "morie_otis_analyze_c02" ] }, { "page": "morie_otis_analyze_c02_ruhela_aggregate", "title": "c02 aggregate Ruhela: Female -> RC (institution GEE).", "topics": [ "morie_otis_analyze_c02_mrm_aggregate", "morie_otis_analyze_c02_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c03", "title": "Individuals x race x gender (c03)", "topics": [ "morie_otis_analyze_c03" ] }, { "page": "morie_otis_analyze_c03_ruhela_aggregate", "title": "c03 aggregate Ruhela: Indigenous -> RC.", "topics": [ "morie_otis_analyze_c03_mrm_aggregate", "morie_otis_analyze_c03_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c04", "title": "Individuals in RC/seg by race x region (c04)", "topics": [ "morie_otis_analyze_c04" ] }, { "page": "morie_otis_analyze_c04_ruhela_aggregate", "title": "c04 aggregate Ruhela: Indigenous -> RC (by region).", "topics": [ "morie_otis_analyze_c04_mrm_aggregate", "morie_otis_analyze_c04_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c04_ruhela_aggregate_region_cluster", "title": "c04 region-cluster variant.", "topics": [ "morie_otis_analyze_c04_mrm_aggregate_region_cluster", "morie_otis_analyze_c04_ruhela_aggregate_region_cluster" ] }, { "page": "morie_otis_analyze_c05", "title": "Individuals in RC/seg by religion x region (c05)", "topics": [ "morie_otis_analyze_c05" ] }, { "page": "morie_otis_analyze_c05_ruhela_aggregate", "title": "c05 aggregate Ruhela: non-majority religion -> RC.", "topics": [ "morie_otis_analyze_c05_mrm_aggregate", "morie_otis_analyze_c05_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c06", "title": "Individuals in RC/seg by age category x region (c06)", "topics": [ "morie_otis_analyze_c06" ] }, { "page": "morie_otis_analyze_c06_ruhela_aggregate", "title": "c06 aggregate Ruhela: Age 50+ -> RC.", "topics": [ "morie_otis_analyze_c06_mrm_aggregate", "morie_otis_analyze_c06_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c07", "title": "Individuals x alerts x gender (c07)", "topics": [ "morie_otis_analyze_c07" ] }, { "page": "morie_otis_analyze_c07_ruhela_aggregate", "title": "c07 aggregate Ruhela: Alert presence x Gender -> RC.", "topics": [ "morie_otis_analyze_c07_mrm_aggregate", "morie_otis_analyze_c07_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c08", "title": "Individuals by religion x gender (c08)", "topics": [ "morie_otis_analyze_c08" ] }, { "page": "morie_otis_analyze_c08_ruhela_aggregate", "title": "c08 aggregate Ruhela: non-majority religion x gender -> RC.", "topics": [ "morie_otis_analyze_c08_mrm_aggregate", "morie_otis_analyze_c08_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c09", "title": "Individuals by age category x gender (c09)", "topics": [ "morie_otis_analyze_c09" ] }, { "page": "morie_otis_analyze_c09_ruhela_aggregate", "title": "c09 aggregate Ruhela: Age 50+ x gender -> RC.", "topics": [ "morie_otis_analyze_c09_mrm_aggregate", "morie_otis_analyze_c09_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c10", "title": "RC/seg aggregate durations by institution (c10)", "topics": [ "morie_otis_analyze_c10" ] }, { "page": "morie_otis_analyze_c10_ruhela_aggregate", "title": "c10 aggregate Ruhela: Female -> median RC days (institution GEE).", "topics": [ "morie_otis_analyze_c10_mrm_aggregate", "morie_otis_analyze_c10_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c11", "title": "Individuals by aggregate-duration bin (c11)", "topics": [ "morie_otis_analyze_c11" ] }, { "page": "morie_otis_analyze_c11_mandela_classification", "title": "Mandela-RF on c11 - per-individual Mandela classification by year.", "topics": [ "morie_otis_analyze_c11_mandela_classification" ] }, { "page": "morie_otis_analyze_c11_ruhela_aggregate", "title": "c11 aggregate Ruhela: long-duration bin (>=16 days) -> RC.", "topics": [ "morie_otis_analyze_c11_mrm_aggregate", "morie_otis_analyze_c11_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_c12", "title": "RC/seg aggregate durations by region & gender (c12)", "topics": [ "morie_otis_analyze_c12" ] }, { "page": "morie_otis_analyze_c12_ruhela_aggregate", "title": "c12 aggregate Ruhela: Female -> median RC days (by region).", "topics": [ "morie_otis_analyze_c12_mrm_aggregate", "morie_otis_analyze_c12_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_d_chi2", "title": "MRM chi-square family on d-series.", "topics": [ "morie_otis_analyze_d_chi2" ] }, { "page": "morie_otis_analyze_d01", "title": "Person-level custodial deaths (d01)", "topics": [ "morie_otis_analyze_d01" ] }, { "page": "morie_otis_analyze_d02", "title": "Custodial deaths by gender (d02)", "topics": [ "morie_otis_analyze_d02" ] }, { "page": "morie_otis_analyze_d02_ruhela_aggregate", "title": "d02 aggregate Ruhela: Female -> custodial deaths.", "topics": [ "morie_otis_analyze_d02_mrm_aggregate", "morie_otis_analyze_d02_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_d03", "title": "Custodial deaths by race (d03)", "topics": [ "morie_otis_analyze_d03" ] }, { "page": "morie_otis_analyze_d03_ruhela_aggregate", "title": "d03 aggregate Ruhela: Indigenous -> custodial deaths.", "topics": [ "morie_otis_analyze_d03_mrm_aggregate", "morie_otis_analyze_d03_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_d04", "title": "Custodial deaths by religion (d04)", "topics": [ "morie_otis_analyze_d04" ] }, { "page": "morie_otis_analyze_d04_ruhela_aggregate", "title": "d04 aggregate Ruhela: non-majority religion -> custodial deaths.", "topics": [ "morie_otis_analyze_d04_mrm_aggregate", "morie_otis_analyze_d04_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_d05", "title": "Custodial deaths by age category (d05)", "topics": [ "morie_otis_analyze_d05" ] }, { "page": "morie_otis_analyze_d05_ruhela_aggregate", "title": "d05 aggregate Ruhela: Age 50+ -> custodial deaths.", "topics": [ "morie_otis_analyze_d05_mrm_aggregate", "morie_otis_analyze_d05_ruhela_aggregate" ] }, { "page": "morie_otis_analyze_d06", "title": "Custodial deaths by alert x medical cause (d06)", "topics": [ "morie_otis_analyze_d06" ] }, { "page": "morie_otis_analyze_d07", "title": "Custodial deaths by alert x housing unit (d07)", "topics": [ "morie_otis_analyze_d07" ] }, { "page": "morie_otis_analyze_otis_mandela_provincial_vs_federal", "title": "Mandela-RF cross-comparison: Ontario provincial vs federal SIU.", "topics": [ "morie_otis_analyze_otis_mandela_provincial_vs_federal" ] }, { "page": "morie_otis_analyze_ruhela_grid", "title": "Aggregate Ruhela grid: one-page IRR comparison across analyzers.", "topics": [ "morie_otis_analyze_ruhela_grid" ] }, { "page": "morie_otis_analyze_ruhela_master", "title": "Paper-ready master report - every Ruhela formulation in one result.", "topics": [ "morie_otis_analyze_ruhela_master" ] }, { "page": "morie_otis_analyze_ruhela_per_year", "title": "Per-fiscal-year full-DLRM Ruhela formulation driver.", "topics": [ "morie_otis_analyze_ruhela_per_year" ] }, { "page": "morie_otis_analyzers", "title": "Registry of dataset-id -> analyzer", "topics": [ "morie_otis_analyzers" ] }, { "page": "morie_otis_astcmb", "title": "Alert-state combination encoding (8 combos -> complexity index)", "topics": [ "morie_otis_astcmb" ] }, { "page": "morie_otis_causal_grid", "title": "Run IPW / AIPW / IRM-DML on the three canonical (T, Y) pairs.", "topics": [ "morie_otis_causal_grid" ] }, { "page": "morie_otis_churn", "title": "Goffmanian institutional-churn analyses on OTIS", "topics": [ "morie_otis_churn" ] }, { "page": "morie_otis_churn_analyze_all", "title": "Run all 11 OTIS-churn analyses", "topics": [ "morie_otis_churn_analyze_all" ] }, { "page": "morie_otis_classify_mandela_combo", "title": "Mandela alert-state classifier for an OTIS placement row.", "topics": [ "morie_otis_classify_mandela_combo" ] }, { "page": "morie_otis_disciplinary_medical_overlap", "title": "Disciplinary x medical-protection overlap", "topics": [ "morie_otis_disciplinary_medical_overlap" ] }, { "page": "morie_otis_embedding_distribution", "title": "Total-days embedding distribution (lognormal vs Pareto vs exp)", "topics": [ "morie_otis_embedding_distribution" ] }, { "page": "morie_otis_intra_year_transition_matrix", "title": "Intra-year region-to-region transition matrix", "topics": [ "morie_otis_intra_year_transition_matrix" ] }, { "page": "morie_otis_ipw_ate", "title": "Hajek-stabilised IPW estimator of the ATE on OTIS data.", "topics": [ "morie_otis_ipw_ate" ] }, { "page": "morie_otis_irm_dml", "title": "Interactive Regression Model DML on OTIS data (ATE, ATTE, ATC).", "topics": [ "morie_otis_irm_dml" ] }, { "page": "morie_otis_irr_glmm_vm", "title": "Poisson + Negative-Binomial IRR for volatility ~ alert complexity", "topics": [ "morie_otis_irr_glmm_vm" ] }, { "page": "morie_otis_load", "title": "Load the canonical OTIS CSV", "topics": [ "morie_otis_load" ] }, { "page": "morie_otis_make_pair_a", "title": "Pair (a): MentalHealth_Alert -> SuicideRisk_Alert (binary -> binary).", "topics": [ "morie_otis_make_pair_a" ] }, { "page": "morie_otis_make_pair_alert_to_volatility_a01", "title": "a01-aware wrapper for the Ruhela alert -> volatility builder.", "topics": [ "morie_otis_make_pair_alert_to_volatility_a01" ] }, { "page": "morie_otis_make_pair_alert_to_volatility_all", "title": "Run both Ruhela and Naive alert -> volatility builders.", "topics": [ "morie_otis_make_pair_alert_to_volatility_all" ] }, { "page": "morie_otis_make_pair_alert_to_volatility_naive", "title": "Naive (max-simultaneous-flags + binary vm) alert -> volatility builder.", "topics": [ "morie_otis_make_pair_alert_to_volatility_naive" ] }, { "page": "morie_otis_make_pair_alert_to_volatility_ruhela", "title": "Ruhela's primary alert-complexity -> regional-volatility builder.", "topics": [ "morie_otis_make_pair_alert_to_volatility_ruhela" ] }, { "page": "morie_otis_make_pair_b", "title": "Pair (b): HighAlertComplexity -> AnyReadmission.", "topics": [ "morie_otis_make_pair_b" ] }, { "page": "morie_otis_make_pair_c", "title": "Pair (c): RegionalVolatility -> SegregationDays.", "topics": [ "morie_otis_make_pair_c" ] }, { "page": "morie_otis_mortification_cooccurrence", "title": "Mortification co-occurrence (concurrent alerts)", "topics": [ "morie_otis_mortification_cooccurrence" ] }, { "page": "morie_otis_otdesc", "title": "Full OTIS descriptive statistics suite", "topics": [ "morie_otis_otdesc" ] }, { "page": "morie_otis_otdml", "title": "Cross-fitted partially linear DML (ATE/ATT) on OTIS", "topics": [ "morie_otis_otdml" ] }, { "page": "morie_otis_path_complexity_gini", "title": "Path complexity Gini by (year, region)", "topics": [ "morie_otis_path_complexity_gini" ] }, { "page": "morie_otis_pipeline", "title": "OTIS analysis pipeline (RichResult-style driver)", "topics": [ "morie_otis_pipeline" ] }, { "page": "morie_otis_plr", "title": "Partially Linear Regression DML on OTIS (not yet ported).", "topics": [ "morie_otis_plr" ] }, { "page": "morie_otis_primitives", "title": "Ontario Restrictive Confinement (OTIS) primitive analyses", "topics": [ "morie_otis_alert_state_combo", "morie_otis_descriptives", "morie_otis_dml", "morie_otis_primitives", "morie_otis_rc_trends", "morie_otis_regional_placement", "morie_otis_volatility" ] }, { "page": "morie_otis_psm", "title": "Propensity-score 1:k NN matching with caliper (not yet ported).", "topics": [ "morie_otis_psm" ] }, { "page": "morie_otis_psm_subclass", "title": "Propensity-score subclassification ATE (not yet ported).", "topics": [ "morie_otis_psm_subclass" ] }, { "page": "morie_otis_rctrnd", "title": "Restrictive-confinement trends over time by region", "topics": [ "morie_otis_rctrnd" ] }, { "page": "morie_otis_regC_demog_contingency", "title": "Multi-region path x Gender / Age contingency", "topics": [ "morie_otis_regC_demog_contingency" ] }, { "page": "morie_otis_region_alert_state_richness", "title": "Region x alert state richness", "topics": [ "morie_otis_region_alert_state_richness" ] }, { "page": "morie_otis_repeat_placement_concentration", "title": "Repeat-placement concentration (Goffmanian cyclical-inmate)", "topics": [ "morie_otis_repeat_placement_concentration" ] }, { "page": "morie_otis_rplace", "title": "Regional placement matrix by age group", "topics": [ "morie_otis_rplace" ] }, { "page": "morie_otis_tps_analyze_all", "title": "Run all OTIS-TPS overlay analyses", "topics": [ "morie_otis_tps_analyze_all" ] }, { "page": "morie_otis_tps_composite_overlay", "title": "Composite overlay (alias for the YoY correlation)", "topics": [ "morie_otis_tps_composite_overlay" ] }, { "page": "morie_otis_tps_overlay", "title": "Cross-link OTIS (Ontario corrections) with TPS (Toronto police) data", "topics": [ "morie_otis_tps_overlay" ] }, { "page": "morie_otis_tps_per_region_rollup", "title": "OTIS seg/RC totals per region x year (Toronto row flagged for TPS-overlay use)", "topics": [ "morie_otis_tps_per_region_rollup" ] }, { "page": "morie_otis_tps_yoy_correlation", "title": "Year-over-year correlation between OTIS Toronto-region segregation placements and TPS incident counts (per category)", "topics": [ "morie_otis_tps_yoy_correlation" ] }, { "page": "morie_otis_volat", "title": "Regional volatility / placement movement", "topics": [ "morie_otis_volat" ] }, { "page": "morie_otis_within_year_placement_count", "title": "Within-year placement-count distribution", "topics": [ "morie_otis_within_year_placement_count" ] }, { "page": "morie_otis_within_year_region_diversity", "title": "Within-year region diversity", "topics": [ "morie_otis_within_year_region_diversity" ] }, { "page": "morie_paired_t_test", "title": "Paired t-test", "topics": [ "morie_paired_t_test" ] }, { "page": "morie_parse_nypd_law_code", "title": "Parse an NYPD 'law_code' string into its structural fields", "topics": [ "morie_parse_nypd_law_code" ] }, { "page": "morie_paths", "title": "Resolve standard project paths", "topics": [ "morie_paths" ] }, { "page": "morie_pca_dimension_reduction", "title": "PCA via SVD for dimension reduction (R parity)", "topics": [ "morie_pca_dimension_reduction" ] }, { "page": "morie_pcg_filter", "title": "Phonocardiogram (PCG) bandpass filter", "topics": [ "morie_pcg_filter" ] }, { "page": "morie_penalized_regression", "title": "Elastic-net regression via coordinate descent (base R)", "topics": [ "morie_penalized_regression" ] }, { "page": "morie_percentile_modified_rank", "title": "Percentile-modified rank (Gastwirth) two-sample test (Gibbons Ch 8.3.3)", "topics": [ "morie_percentile_modified_rank" ] }, { "page": "morie_performance_check_collinearity", "title": "Collinearity / VIF check via 'performance'", "topics": [ "morie_performance_check_collinearity" ] }, { "page": "morie_performance_check_model", "title": "Regression-diagnostic plots via 'performance'", "topics": [ "morie_performance_check_model" ] }, { "page": "morie_performance_check_outliers", "title": "Outlier check via 'performance'", "topics": [ "morie_performance_check_outliers" ] }, { "page": "morie_performance_r2", "title": "R-squared family via 'performance'", "topics": [ "morie_performance_r2" ] }, { "page": "morie_point_biserial_r", "title": "Point-biserial correlation", "topics": [ "morie_point_biserial_r" ] }, { "page": "morie_polynomial_regression", "title": "Polynomial regression (R parity)", "topics": [ "morie_polynomial_regression" ] }, { "page": "morie_power_prop_test", "title": "Power for a two-proportion z-test", "topics": [ "morie_power_prop_test" ] }, { "page": "morie_power_t_test", "title": "Power for a two-sample t-test", "topics": [ "morie_power_t_test" ] }, { "page": "morie_ppcor_partial", "title": "Partial correlation via 'ppcor'", "topics": [ "morie_ppcor_partial" ] }, { "page": "morie_ppcor_semipartial", "title": "Semi-partial correlation via 'ppcor'", "topics": [ "morie_ppcor_semipartial" ] }, { "page": "morie_pps_sample", "title": "Probability proportional to size (PPS) sampling", "topics": [ "morie_pps_sample" ] }, { "page": "morie_prediction_accuracy", "title": "Genomic-prediction accuracy metrics", "topics": [ "morie_prediction_accuracy" ] }, { "page": "morie_predpol_aggregate_areas", "title": "Aggregate per-record predictive-policing data to one row per area", "topics": [ "morie_predpol_aggregate_areas" ] }, { "page": "morie_predpol_calibration_audit", "title": "Audit whether an algorithm's area risk ranking matches realised outcomes", "topics": [ "morie_predpol_calibration_audit" ] }, { "page": "morie_predpol_score_disparity", "title": "Descriptive disparity in a risk score across groups", "topics": [ "morie_predpol_score_disparity" ] }, { "page": "morie_predpol_temporal_audit", "title": "Audit how disparity metrics move over time and across cities", "topics": [ "morie_predpol_temporal_audit" ] }, { "page": "morie_profile_dataset", "title": "Profile a data.frame: per-column types, missingness, summary statistics", "topics": [ "morie_profile_dataset" ] }, { "page": "morie_prophet_components", "title": "Prophet-style additive decomposition (linear trend + Fourier seasonality)", "topics": [ "morie_prophet_components" ] }, { "page": "morie_proportion_ci", "title": "Wilson score confidence interval for a proportion", "topics": [ "morie_proportion_ci" ] }, { "page": "morie_psymet_alpha", "title": "Cronbach's coefficient alpha with Feldt CI", "topics": [ "morie_psymet_alpha" ] }, { "page": "morie_psymet_alphadel", "title": "Alpha if item deleted", "topics": [ "morie_psymet_alphadel" ] }, { "page": "morie_psymet_ave", "title": "Average variance extracted (AVE) from factor loadings. Mean(lambda^2).", "topics": [ "morie_psymet_ave" ] }, { "page": "morie_psymet_bartlett", "title": "Bartlett's test of sphericity.", "topics": [ "morie_psymet_bartlett" ] }, { "page": "morie_psymet_cr", "title": "Composite reliability from standardized factor loadings. CR = (sum lambda)^2 / ((sum lambda)^2 + sum(1 - lambda^2))", "topics": [ "morie_psymet_cr" ] }, { "page": "morie_psymet_discrimination", "title": "Item discrimination (D-statistic).", "topics": [ "morie_psymet_discrimination" ] }, { "page": "morie_psymet_itemtotal", "title": "Corrected item-total correlations", "topics": [ "morie_psymet_itemtotal" ] }, { "page": "morie_psymet_kmo", "title": "Kaiser-Meyer-Olkin sampling adequacy.", "topics": [ "morie_psymet_kmo" ] }, { "page": "morie_psymet_omega", "title": "McDonald's omega total and hierarchical", "topics": [ "morie_psymet_omega" ] }, { "page": "morie_psymet_parallel", "title": "Horn's parallel analysis - suggested number of factors.", "topics": [ "morie_psymet_parallel" ] }, { "page": "morie_psymet_splithalf", "title": "Spearman-Brown split-half reliability.", "topics": [ "morie_psymet_splithalf" ] }, { "page": "morie_quantile_reg", "title": "Quantile regression via 'quantreg'", "topics": [ "morie_quantile_reg" ] }, { "page": "morie_random_forest_ensemble", "title": "Random Forest ensemble (R parity)", "topics": [ "morie_random_forest_ensemble" ] }, { "page": "morie_random_forest_genomic", "title": "Random-forest genomic predictor", "topics": [ "morie_random_forest_genomic" ] }, { "page": "morie_random_search_cv", "title": "Random search hyperparameter optimisation (R parity)", "topics": [ "morie_random_search_cv" ] }, { "page": "morie_randtests_bartels", "title": "Bartels rank test via 'randtests'", "topics": [ "morie_randtests_bartels" ] }, { "page": "morie_randtests_runs", "title": "Wald-Wolfowitz runs test via 'randtests'", "topics": [ "morie_randtests_runs" ] }, { "page": "morie_randtests_turning_point", "title": "Turning-point test via 'randtests'", "topics": [ "morie_randtests_turning_point" ] }, { "page": "morie_rank_based_test", "title": "Mann's rank test for randomness (Gibbons Ch 3.5)", "topics": [ "morie_rank_based_test" ] }, { "page": "morie_rank_order_statistics", "title": "Signed ranks of paired differences (Gibbons Ch 5.5)", "topics": [ "morie_rank_order_statistics" ] }, { "page": "morie_rank_placements", "title": "Rank placements of Y among X order statistics (Gibbons Ch 2.11.3)", "topics": [ "morie_rank_placements" ] }, { "page": "morie_rdd_bandwidth_cct", "title": "Calonico-Cattaneo-Titiunik (CCT) MSE-optimal bandwidth", "topics": [ "morie_rdd_bandwidth_cct" ] }, { "page": "morie_rdd_bandwidth_ik", "title": "Imbens-Kalyanaraman (IK) MSE-optimal bandwidth", "topics": [ "morie_rdd_bandwidth_ik" ] }, { "page": "morie_rdd_bandwidth_rot", "title": "Rule-of-thumb (ROT) bandwidth - Silverman-style on running variable", "topics": [ "morie_rdd_bandwidth_rot" ] }, { "page": "morie_rdd_bandwidth_sensitivity", "title": "Bandwidth sensitivity sweep", "topics": [ "morie_rdd_bandwidth_sensitivity" ] }, { "page": "morie_rdd_bias_corrected", "title": "CCT bias-corrected, robust-SE RDD inference", "topics": [ "morie_rdd_bias_corrected" ] }, { "page": "morie_rdd_cattaneo_density", "title": "Cattaneo-Jansson-Ma (2020) local-polynomial density test", "topics": [ "morie_rdd_cattaneo_density" ] }, { "page": "morie_rdd_covariate_balance", "title": "Covariate balance at the cutoff", "topics": [ "morie_rdd_covariate_balance" ] }, { "page": "morie_rdd_density_test", "title": "McCrary-style RD density test via 'rddensity'", "topics": [ "morie_rdd_density_test" ] }, { "page": "morie_rdd_discrete", "title": "RDD with discrete running variable", "topics": [ "morie_rdd_discrete" ] }, { "page": "morie_rdd_donut", "title": "Donut-hole RDD", "topics": [ "morie_rdd_donut" ] }, { "page": "morie_rdd_fuzzy", "title": "Fuzzy RDD treatment effect via instrumented Wald ratio", "topics": [ "morie_rdd_fuzzy" ] }, { "page": "morie_rdd_geographic", "title": "Geographic / boundary RDD on a signed distance", "topics": [ "morie_rdd_geographic" ] }, { "page": "morie_rdd_kernels", "title": "RDD kernel functions", "topics": [ "morie_rdd_kernels", "morie_rdd_kernel_epanechnikov", "morie_rdd_kernel_gaussian", "morie_rdd_kernel_triangular", "morie_rdd_kernel_uniform" ] }, { "page": "morie_rdd_kink", "title": "Regression kink design - slope discontinuity at the cutoff", "topics": [ "morie_rdd_kink" ] }, { "page": "morie_rdd_local_polynomial", "title": "Local polynomial regression at user-supplied evaluation points", "topics": [ "morie_rdd_local_polynomial" ] }, { "page": "morie_rdd_local_randinf", "title": "Local-randomisation RDD inference via 'rdlocrand'", "topics": [ "morie_rdd_local_randinf" ] }, { "page": "morie_rdd_local_randomisation", "title": "Local-randomisation RDD via permutation in a fixed window", "topics": [ "morie_rdd_local_randomisation" ] }, { "page": "morie_rdd_mccrary", "title": "McCrary (2008) density manipulation test", "topics": [ "morie_rdd_mccrary" ] }, { "page": "morie_rdd_placebo_cutoff", "title": "Placebo cutoff falsification test", "topics": [ "morie_rdd_placebo_cutoff" ] }, { "page": "morie_rdd_plot_data", "title": "Binned scatter + global-polynomial data for an RD plot", "topics": [ "morie_rdd_plot_data" ] }, { "page": "morie_rdd_power", "title": "RDD power calculation", "topics": [ "morie_rdd_power" ] }, { "page": "morie_rdd_power_calc", "title": "Power calculations for RDD designs via 'rdpower'", "topics": [ "morie_rdd_power_calc" ] }, { "page": "morie_rdd_sample_size", "title": "RDD sample-size determination", "topics": [ "morie_rdd_sample_size" ] }, { "page": "morie_rdd_sharp", "title": "Sharp RDD treatment effect at the cutoff", "topics": [ "morie_rdd_sharp" ] }, { "page": "morie_read_outputs_manifest", "title": "Read outputs manifest from a project", "topics": [ "morie_read_outputs_manifest" ] }, { "page": "morie_recommended_pair_test", "title": "Recommended bivariate test for a pair of variables.", "topics": [ "morie_recommended_pair_test" ] }, { "page": "morie_recommended_summary", "title": "Recommended summary statistic for a single variable.", "topics": [ "morie_recommended_summary" ] }, { "page": "morie_regime_switching", "title": "Markov-switching regression (Hamilton 1989)", "topics": [ "morie_regime_switching" ] }, { "page": "morie_regularization_path", "title": "Ridge / LASSO / ElasticNet regularization path (R parity)", "topics": [ "morie_regularization_path" ] }, { "page": "morie_risk_difference_ci", "title": "Risk difference (ARD) with Newcombe CI", "topics": [ "morie_risk_difference_ci" ] }, { "page": "morie_risk_ratio_ci", "title": "Risk ratio (relative risk) with log-normal CI", "topics": [ "morie_risk_ratio_ci" ] }, { "page": "morie_rkhs_full", "title": "RKHS regression with Gaussian kernel", "topics": [ "morie_rkhs_full" ] }, { "page": "morie_rnn_genomic", "title": "Vanilla RNN genomic predictor (BPTT, base R)", "topics": [ "morie_rnn_genomic" ] }, { "page": "morie_roc_auc_score", "title": "ROC curve and AUC (R parity)", "topics": [ "morie_roc_auc_score" ] }, { "page": "morie_rsample_bootstraps", "title": "Direct bridge to 'rsample::bootstraps'", "topics": [ "morie_rsample_bootstraps" ] }, { "page": "morie_run_ebac_selection_ipw_analysis", "title": "Run the eBAC selection-adjusted IPW workflow", "topics": [ "morie_run_ebac_selection_ipw_analysis" ] }, { "page": "morie_run_morie_module", "title": "Run one implemented MORIE module against CPADS data", "topics": [ "morie_run_morie_module" ] }, { "page": "morie_run_morie_modules", "title": "Run multiple implemented MORIE modules", "topics": [ "morie_run_morie_modules" ] }, { "page": "morie_run_pipeline", "title": "Run multiple workflow steps", "topics": [ "morie_run_pipeline" ] }, { "page": "morie_run_propensity_ipw_analysis", "title": "Run the CPADS propensity/IPW workflow", "topics": [ "morie_run_propensity_ipw_analysis" ] }, { "page": "morie_run_treatment_effects_analysis", "title": "Run a treatment-effects analysis (point estimate, SE, 95% CI)", "topics": [ "morie_run_treatment_effects_analysis" ] }, { "page": "morie_run_weighted_logistic_analysis", "title": "Run a weighted logistic-regression analysis", "topics": [ "morie_run_weighted_logistic_analysis" ] }, { "page": "morie_run_workflow_step", "title": "Run one project workflow step", "topics": [ "morie_run_workflow_step" ] }, { "page": "morie_sample", "title": "Load a bundled MORIE reference sample by name", "topics": [ "morie_sample" ] }, { "page": "morie_sample_size_logistic", "title": "Sample size for logistic regression detecting a target odds ratio", "topics": [ "morie_sample_size_logistic" ] }, { "page": "morie_semipar_bridge", "title": "Semiparametric kernel primitives (R port)", "topics": [ "morie_semipar_bridge" ] }, { "page": "morie_sensitivity_evalue", "title": "E-values for the EValue dispatch family (extender)", "topics": [ "morie_sensitivity_evalue" ] }, { "page": "morie_sensitivity_konfound", "title": "Konfound robustness for a coefficient (konfound extender)", "topics": [ "morie_sensitivity_konfound" ] }, { "page": "morie_sensitivity_omitted_var_bias", "title": "Omitted-variable bias on a fitted model (sensemakr extender)", "topics": [ "morie_sensitivity_omitted_var_bias" ] }, { "page": "morie_sensitivity_rosenbaum", "title": "Rosenbaum bounds sensitivity analysis", "topics": [ "morie_sensitivity_rosenbaum" ] }, { "page": "morie_sensitivity_tipping_point", "title": "Tipping-point sensitivity to a single unmeasured confounder (tipr)", "topics": [ "morie_sensitivity_tipping_point" ] }, { "page": "morie_sgolay_smooth", "title": "Savitzky-Golay smoothing filter", "topics": [ "morie_sgolay_smooth" ] }, { "page": "morie_shapiro_wilk_test", "title": "Shapiro-Wilk normality test", "topics": [ "morie_shapiro_wilk_test" ] }, { "page": "morie_sign_test_power", "title": "Power function of the two-sided sign test (Gibbons Ch 5.4.4)", "topics": [ "morie_sign_test_power" ] }, { "page": "morie_simple_random_sample", "title": "Simple random sample from a data frame", "topics": [ "morie_simple_random_sample" ] }, { "page": "morie_simpleboot_two", "title": "Direct bridge to 'simpleboot::two.boot'", "topics": [ "morie_simpleboot_two" ] }, { "page": "morie_simulate_longitudinal_panel", "title": "Simulate a longitudinal panel and return a tidy long-format data.frame", "topics": [ "morie_simulate_longitudinal_panel" ] }, { "page": "morie_siu_all_analyses", "title": "Run every SIU descriptive analysis in this module", "topics": [ "morie_siu_all_analyses" ] }, { "page": "morie_siu_analyze", "title": "SIU descriptive analyses (R port of 'morie.siu.analyze')", "topics": [ "morie_siu_analyze" ] }, { "page": "morie_siu_anomaly_check", "title": "Per-field anomaly check: does the parser's extraction match the HTML?", "topics": [ "morie_siu_anomaly_check" ] }, { "page": "morie_siu_audit_case", "title": "Audit one SIU case end-to-end: parser output + raw HTML", "topics": [ "morie_siu_audit_case" ] }, { "page": "morie_siu_audit_columns", "title": "Per-column accuracy audit: estimate every SIU column's correctness", "topics": [ "morie_siu_audit_columns" ] }, { "page": "morie_siu_by_police_service", "title": "SIU cases by police service", "topics": [ "morie_siu_by_police_service" ] }, { "page": "morie_siu_by_year", "title": "SIU cases by year", "topics": [ "morie_siu_by_year" ] }, { "page": "morie_siu_cache_path", "title": "Cache-path helper for the lightweight SIU scraper", "topics": [ "morie_siu_cache_path" ] }, { "page": "morie_siu_case_counts", "title": "SIU per-case team-size distribution", "topics": [ "morie_siu_case_counts" ] }, { "page": "morie_siu_charges_by_year_chi2", "title": "Chi-square: charges-recommended independent of year?", "topics": [ "morie_siu_charges_by_year_chi2" ] }, { "page": "morie_siu_classify_mandela", "title": "Apply the Sprott-Doob Mandela-Rules classifier to one SIU stay", "topics": [ "morie_siu_classify_mandela" ] }, { "page": "morie_siu_compare", "title": "Field-by-field SIU comparison against a user-supplied external table", "topics": [ "morie_siu_compare" ] }, { "page": "morie_siu_decision_timing", "title": "SIU decision-timing distributions", "topics": [ "morie_siu_decision_timing" ] }, { "page": "morie_siu_demographics", "title": "Affected-person demographics", "topics": [ "morie_siu_demographics" ] }, { "page": "morie_siu_fetch", "title": "Lightweight Ontario SIU Director's Reports scraper (R-native)", "topics": [ "morie_siu_fetch", "morie_siu_index_url" ] }, { "page": "morie_siu_fetch_cases", "title": "Scrape Ontario SIU Director's Reports into a tidy CSV", "topics": [ "morie_siu_fetch_cases" ] }, { "page": "morie_siu_fetch_dataframe", "title": "Scrape Ontario SIU Director's Reports and return a data frame", "topics": [ "morie_siu_fetch_dataframe" ] }, { "page": "morie_siu_index", "title": "SIU drid → case_number → language index", "topics": [ "morie_siu_index" ] }, { "page": "morie_siu_llm_extract", "title": "Extract SIU report fields with an LLM (Gemini or Claude)", "topics": [ "morie_siu_llm_extract" ] }, { "page": "morie_siu_mental_health_race_indicators", "title": "Mental-health / race keyword indicators", "topics": [ "morie_siu_mental_health_race_indicators" ] }, { "page": "morie_siu_parse_html", "title": "Parse a SIU director's-report HTML page (pure-R)", "topics": [ "morie_siu_parse_html" ] }, { "page": "morie_siu_parse_news_html", "title": "Parse a SIU news-release HTML page (pure-R)", "topics": [ "morie_siu_parse_news_html" ] }, { "page": "morie_siu_parser", "title": "Pure-R SIU director's-report parser (port of 'morie.siu._parser')", "topics": [ "morie_siu_parser" ] }, { "page": "morie_siu_record_correction", "title": "Record a verified correction to the SIU parser's output", "topics": [ "morie_siu_record_correction" ] }, { "page": "morie_siu_refresh_manifest", "title": "Rebuild the Ontario SIU DRID manifest by probing the live site", "topics": [ "morie_siu_refresh_manifest" ] }, { "page": "morie_siu_sanity_check", "title": "Row-level sanity check on a parsed SIU table (regex-only, no LLM)", "topics": [ "morie_siu_sanity_check" ] }, { "page": "morie_siu_sprott_doob_feb2021", "title": "Comprehensive replication of Sprott & Doob (Feb 2021)", "topics": [ "morie_siu_sprott_doob_feb2021" ] }, { "page": "morie_siu_sprott_doob_iftene_table1", "title": "Sprott-Doob-Iftene (May 2021) Table 1: IEDM-reviewed population", "topics": [ "morie_siu_sprott_doob_iftene_table1" ] }, { "page": "morie_siu_sprott_doob_iftene_table10", "title": "Sprott-Doob-Iftene (May 2021) Table 10: per-IEDM decision variance", "topics": [ "morie_siu_sprott_doob_iftene_table10" ] }, { "page": "morie_siu_sprott_doob_iftene_table15", "title": "Sprott-Doob-Iftene (May 2021) Table 15: long-stay no-IEDM cases", "topics": [ "morie_siu_sprott_doob_iftene_table15" ] }, { "page": "morie_siu_sprott_doob_iftene_table9", "title": "Sprott-Doob-Iftene (May 2021) Table 9: IEDM review outcomes", "topics": [ "morie_siu_sprott_doob_iftene_table9" ] }, { "page": "morie_siu_sprott_doob_table11", "title": "Sprott-Doob (Feb 2021) Table 11: Region x stay length", "topics": [ "morie_siu_sprott_doob_table11" ] }, { "page": "morie_siu_sprott_doob_table12", "title": "Sprott-Doob (Feb 2021) Table 12: regional over-/under-representation", "topics": [ "morie_siu_sprott_doob_table12" ] }, { "page": "morie_siu_sprott_doob_table13", "title": "Sprott-Doob (Feb 2021) Table 13: regional SIU person-stay rates", "topics": [ "morie_siu_sprott_doob_table13" ] }, { "page": "morie_siu_sprott_doob_table15", "title": "Sprott-Doob (Feb 2021) Table 15: Region x MH-flag", "topics": [ "morie_siu_sprott_doob_table15" ] }, { "page": "morie_siu_sprott_doob_table19", "title": "Sprott-Doob (Feb 2021) Table 19: Mandela-Rules classification", "topics": [ "morie_siu_sprott_doob_table19" ] }, { "page": "morie_siu_sprott_doob_table22", "title": "Sprott-Doob (Feb 2021) Table 22: Region x Mandela groups", "topics": [ "morie_siu_sprott_doob_table22" ] }, { "page": "morie_siu_sprott_doob_table23", "title": "Sprott-Doob (Feb 2021) Table 23: regional torture/solitary rates", "topics": [ "morie_siu_sprott_doob_table23" ] }, { "page": "morie_siu_sprott_doob_table4", "title": "Sprott-Doob (Feb 2021) Table 4: length-of-stay distribution", "topics": [ "morie_siu_sprott_doob_table4" ] }, { "page": "morie_siu_translate", "title": "Translate SIU report text into any target language via local LLM", "topics": [ "morie_siu_translate", "morie_siu_translate_fr_to_en" ] }, { "page": "morie_siu_verify_chi2", "title": "Recompute Pearson chi-square from a 2D contingency table", "topics": [ "morie_siu_verify_chi2" ] }, { "page": "morie_siu_verify_published_chi_squares", "title": "Verify every published chi-square against its transcribed cells", "topics": [ "morie_siu_verify_published_chi_squares" ] }, { "page": "MORIE_SIUIAP_AFFIDAVITS", "title": "Federal Court affidavits / expert evidence indexed by 'morie'.", "topics": [ "MORIE_SIUIAP_AFFIDAVITS" ] }, { "page": "morie_siuiap_cite", "title": "Build a citation string for an SIU IAP / CRIMSL / affidavit entry.", "topics": [ "morie_siuiap_cite" ] }, { "page": "MORIE_SIUIAP_CRIMSL_REPORTS", "title": "CRIMSL UToronto Sprott / Doob / Iftene research reports (2020-2021).", "topics": [ "MORIE_SIUIAP_CRIMSL_REPORTS" ] }, { "page": "MORIE_SIUIAP_ORIGINAL_PANEL_2019_2020", "title": "Earlier (Doob-chaired) panel, established 2019, dissolved mid-2020.", "topics": [ "MORIE_SIUIAP_ORIGINAL_PANEL_2019_2020" ] }, { "page": "MORIE_SIUIAP_PANEL_MANDATE", "title": "SIU IAP panel mandate (long-form prose).", "topics": [ "MORIE_SIUIAP_PANEL_MANDATE" ] }, { "page": "MORIE_SIUIAP_PANEL_MEMBERS", "title": "SIU IAP panel members (2021-2024 panel, Sapers-chaired).", "topics": [ "MORIE_SIUIAP_PANEL_MEMBERS" ] }, { "page": "morie_siuiap_panel_summary", "title": "Human-readable summary of the SIU IAP panel.", "topics": [ "morie_siuiap_panel_summary" ] }, { "page": "MORIE_SIUIAP_REPORTS", "title": "SIU IAP panel reports (Public Safety Canada, 2022-2024).", "topics": [ "MORIE_SIUIAP_REPORTS" ] }, { "page": "MORIE_SIUIAP_URL", "title": "SIU IAP - Public Safety Canada landing page URL.", "topics": [ "MORIE_SIUIAP_URL" ] }, { "page": "morie_spatial_voting_aldrich_mckelvey", "title": "Aldrich-McKelvey scaling", "topics": [ "morie_spatial_voting_aldrich_mckelvey" ] }, { "page": "morie_spatial_voting_alpha_nominate", "title": "Alpha-NOMINATE (stub)", "topics": [ "morie_spatial_voting_alpha_nominate" ] }, { "page": "morie_spatial_voting_anchoring_vignettes", "title": "Anchoring vignettes for DIF correction", "topics": [ "morie_spatial_voting_anchoring_vignettes" ] }, { "page": "morie_spatial_voting_bayesian_am", "title": "Bayesian Aldrich-McKelvey scaling (stub)", "topics": [ "morie_spatial_voting_bayesian_am" ] }, { "page": "morie_spatial_voting_bayesian_irt_likelihood", "title": "Bayesian IRT likelihood (deterministic part of CJR machinery)", "topics": [ "morie_spatial_voting_bayesian_irt_likelihood" ] }, { "page": "morie_spatial_voting_bayesian_irt_posterior", "title": "Posterior summaries for a Bayesian IRT chain", "topics": [ "morie_spatial_voting_bayesian_irt_posterior" ] }, { "page": "morie_spatial_voting_bayesian_mds", "title": "Bayesian MDS (stub) - log-normal distances via Metropolis", "topics": [ "morie_spatial_voting_bayesian_mds" ] }, { "page": "morie_spatial_voting_bayesian_unfolding", "title": "Bayesian unfolding (stub) - Bakker & Poole sampler", "topics": [ "morie_spatial_voting_bayesian_unfolding" ] }, { "page": "morie_spatial_voting_blackbox", "title": "Blackbox / Basic Space scaling", "topics": [ "morie_spatial_voting_blackbox" ] }, { "page": "morie_spatial_voting_cjr_irt", "title": "Clinton-Jackman-Rivers Bayesian IRT (stub)", "topics": [ "morie_spatial_voting_cjr_irt" ] }, { "page": "morie_spatial_voting_classical_mds", "title": "Classical (metric) multidimensional scaling", "topics": [ "morie_spatial_voting_classical_mds" ] }, { "page": "morie_spatial_voting_cutting_lines", "title": "Cutting-line endpoints for Coombs-mesh plots", "topics": [ "morie_spatial_voting_cutting_lines" ] }, { "page": "morie_spatial_voting_double_centering", "title": "Double-center a distance matrix", "topics": [ "morie_spatial_voting_double_centering" ] }, { "page": "morie_spatial_voting_dw_nominate", "title": "DW-NOMINATE dynamic weighted ideal-point estimator", "topics": [ "morie_spatial_voting_dw_nominate" ] }, { "page": "morie_spatial_voting_dynamic_irt", "title": "Dynamic IRT with random-walk priors (stub)", "topics": [ "morie_spatial_voting_dynamic_irt" ] }, { "page": "morie_spatial_voting_em_irt", "title": "EM algorithm for binary IRT", "topics": [ "morie_spatial_voting_em_irt" ] }, { "page": "morie_spatial_voting_ideal_point_recovery", "title": "Ideal-point recovery from unfolding output", "topics": [ "morie_spatial_voting_ideal_point_recovery" ] }, { "page": "morie_spatial_voting_indscal", "title": "INDSCAL: weighted MDS with individual differences", "topics": [ "morie_spatial_voting_indscal" ] }, { "page": "morie_spatial_voting_mds_fit_stats", "title": "MDS fit statistics (Mardia criterion)", "topics": [ "morie_spatial_voting_mds_fit_stats" ] }, { "page": "morie_spatial_voting_mlsmu6", "title": "MLSMU6 alternating least-squares unfolding", "topics": [ "morie_spatial_voting_mlsmu6" ] }, { "page": "morie_spatial_voting_nominate_bootstrap", "title": "Parametric bootstrap of NOMINATE standard errors", "topics": [ "morie_spatial_voting_nominate_bootstrap" ] }, { "page": "morie_spatial_voting_nominate_loglik", "title": "NOMINATE log-likelihood and GMP", "topics": [ "morie_spatial_voting_nominate_loglik" ] }, { "page": "morie_spatial_voting_nominate_utility", "title": "NOMINATE Gaussian utility", "topics": [ "morie_spatial_voting_nominate_utility" ] }, { "page": "morie_spatial_voting_nominate_vote_prob", "title": "Single NOMINATE vote probability", "topics": [ "morie_spatial_voting_nominate_vote_prob" ] }, { "page": "morie_spatial_voting_nonmetric_mds", "title": "Nonmetric MDS with isotonic regression", "topics": [ "morie_spatial_voting_nonmetric_mds" ] }, { "page": "morie_spatial_voting_nonparametric_bootstrap", "title": "Nonparametric bootstrap for AM / blackbox scaling positions", "topics": [ "morie_spatial_voting_nonparametric_bootstrap" ] }, { "page": "morie_spatial_voting_normal_vectors", "title": "Normal-vector projection of an external measure", "topics": [ "morie_spatial_voting_normal_vectors" ] }, { "page": "morie_spatial_voting_optimal_classification", "title": "Optimal Classification scaling", "topics": [ "morie_spatial_voting_optimal_classification" ] }, { "page": "morie_spatial_voting_ordered_oc", "title": "Ordered Optimal Classification for ordinal scales", "topics": [ "morie_spatial_voting_ordered_oc" ] }, { "page": "morie_spatial_voting_ordinal_irt", "title": "Ordinal IRT / Quinn factor model (stub)", "topics": [ "morie_spatial_voting_ordinal_irt" ] }, { "page": "morie_spatial_voting_procrustes", "title": "Procrustes rotation", "topics": [ "morie_spatial_voting_procrustes" ] }, { "page": "morie_spatial_voting_smacof", "title": "SMACOF stress minimisation", "topics": [ "morie_spatial_voting_smacof" ] }, { "page": "morie_spatial_voting_smacof_unfolding", "title": "SMACOF rectangular unfolding", "topics": [ "morie_spatial_voting_smacof_unfolding" ] }, { "page": "morie_spatial_voting_unfolding_stress", "title": "Compute unfolding stress", "topics": [ "morie_spatial_voting_unfolding_stress" ] }, { "page": "morie_spatial_voting_wordfish", "title": "Wordfish: Poisson IRT for document-term matrices", "topics": [ "morie_spatial_voting_wordfish" ] }, { "page": "morie_spearman_rho", "title": "Spearman rank correlation", "topics": [ "morie_spearman_rho" ] }, { "page": "morie_specs_from_df", "title": "Build a list of column specs from a parsed CSV header.", "topics": [ "morie_specs_from_df" ] }, { "page": "morie_spectral_cluster", "title": "Spectral clustering via 'kernlab'", "topics": [ "morie_spectral_cluster" ] }, { "page": "morie_spectral_density", "title": "Welch power spectral density", "topics": [ "morie_spectral_density" ] }, { "page": "morie_sprott_doob", "title": "Sprott & Doob (CRIMSL UToronto) SIU analyses", "topics": [ "morie_sprott_doob" ] }, { "page": "morie_stat_bridge", "title": "Bridge between external runners and the morie R command registry", "topics": [ "morie_stat_bridge" ] }, { "page": "morie_stat_commands", "title": "Central command registry for the morie R surface", "topics": [ "morie_stat_commands" ] }, { "page": "morie_state_space_model", "title": "Local-level state-space model (Kalman filter+smoother)", "topics": [ "morie_state_space_model" ] }, { "page": "morie_stratified_sample", "title": "Proportional or fixed stratified random sample", "topics": [ "morie_stratified_sample" ] }, { "page": "morie_suggest_analysis_plan", "title": "Suggest an analysis plan from a dataset profile", "topics": [ "morie_suggest_analysis_plan" ] }, { "page": "morie_sukhatme_test", "title": "Sukhatme two-sample scale test (Gibbons Ch 9.7)", "topics": [ "morie_sukhatme_test" ] }, { "page": "morie_summarize_output_audit", "title": "Summarize an output audit", "topics": [ "morie_summarize_output_audit" ] }, { "page": "morie_survey_calibrate", "title": "Raking calibration to known marginal totals (iterative proportional fitting).", "topics": [ "morie_survey_calibrate" ] }, { "page": "morie_survey_complex_glm", "title": "Complex-survey GLM constructor (single-shot wrapper that builds a design and fits a 'svyglm' in one call). Cluster-robust SEs via the design.", "topics": [ "morie_survey_complex_glm" ] }, { "page": "morie_survey_design", "title": "Construct a survey design object.", "topics": [ "morie_survey_design" ] }, { "page": "morie_survey_glm", "title": "Survey-weighted GLM with design-based SEs.", "topics": [ "morie_survey_glm" ] }, { "page": "morie_survey_hajek_mean", "title": "Hajek (ratio) estimator of a population mean.", "topics": [ "morie_survey_hajek_mean" ] }, { "page": "morie_survey_ht_total", "title": "Horvitz-Thompson estimator of a population total.", "topics": [ "morie_survey_ht_total" ] }, { "page": "morie_survey_mean", "title": "Survey-weighted mean (delegates to 'survey::svymean' when available).", "topics": [ "morie_survey_mean" ] }, { "page": "morie_survey_poststratify", "title": "Post-stratification weights (sample-to-population alignment).", "topics": [ "morie_survey_poststratify" ] }, { "page": "morie_survey_ratio", "title": "Ratio estimator of a population total using known X_pop.", "topics": [ "morie_survey_ratio" ] }, { "page": "morie_survey_subpop", "title": "Subpopulation (domain) mean with Woodruff linearised SE.", "topics": [ "morie_survey_subpop" ] }, { "page": "morie_survival_aft", "title": "Accelerated failure time model (parametric).", "topics": [ "morie_survival_aft" ] }, { "page": "morie_survival_cif", "title": "Cumulative incidence function (Aalen-Johansen) for competing risks.", "topics": [ "morie_survival_cif" ] }, { "page": "morie_survival_compare_parametric", "title": "Compare parametric survival models by AIC/BIC.", "topics": [ "morie_survival_compare_parametric" ] }, { "page": "morie_survival_concordance", "title": "Harrell's concordance index (C-statistic).", "topics": [ "morie_survival_concordance" ] }, { "page": "morie_survival_cox", "title": "Cox proportional hazards model.", "topics": [ "morie_survival_cox" ] }, { "page": "morie_survival_coxsnell", "title": "Cox-Snell residuals from a fitted morie Cox model.", "topics": [ "morie_survival_coxsnell" ] }, { "page": "morie_survival_deviance", "title": "Deviance residuals.", "topics": [ "morie_survival_deviance" ] }, { "page": "morie_survival_finegray", "title": "Fine-Gray subdistribution hazard model (competing risks).", "topics": [ "morie_survival_finegray" ] }, { "page": "morie_survival_hr", "title": "Hazard ratio between two groups via a simple Cox model.", "topics": [ "morie_survival_hr" ] }, { "page": "morie_survival_km", "title": "Kaplan-Meier product-limit survival estimator.", "topics": [ "morie_survival_km" ] }, { "page": "morie_survival_landmark", "title": "Landmark dataset constructor.", "topics": [ "morie_survival_landmark" ] }, { "page": "morie_survival_left_truncated_km", "title": "Left-truncated Kaplan-Meier with delayed entry.", "topics": [ "morie_survival_left_truncated_km" ] }, { "page": "morie_survival_logrank", "title": "Log-rank family tests (logrank / Peto-Peto / Gehan / Tarone-Ware).", "topics": [ "morie_survival_logrank" ] }, { "page": "morie_survival_martingale", "title": "Martingale residuals.", "topics": [ "morie_survival_martingale" ] }, { "page": "morie_survival_nelsonaalen", "title": "Nelson-Aalen cumulative-hazard estimator.", "topics": [ "morie_survival_nelsonaalen" ] }, { "page": "morie_survival_parametric", "title": "Simple parametric survival models (intercept-only).", "topics": [ "morie_survival_parametric" ] }, { "page": "morie_survival_rmst", "title": "Restricted Mean Survival Time (RMST).", "topics": [ "morie_survival_rmst" ] }, { "page": "morie_survival_rmst_diff", "title": "Difference in RMST between two groups.", "topics": [ "morie_survival_rmst_diff" ] }, { "page": "morie_survival_schoenfeld", "title": "Schoenfeld residuals + PH-assumption test.", "topics": [ "morie_survival_schoenfeld" ] }, { "page": "morie_survival_turnbull", "title": "Turnbull NPMLE for interval-censored data.", "topics": [ "morie_survival_turnbull" ] }, { "page": "morie_svm_genomic", "title": "Support-vector regression for genomic prediction", "topics": [ "morie_svm_genomic" ] }, { "page": "morie_svm_hinge_primal", "title": "Linear SVM (primal hinge loss) - R parity", "topics": [ "morie_svm_hinge_primal" ] }, { "page": "morie_svm_kernel_trick", "title": "Kernel SVM (RBF / poly / sigmoid) - R parity", "topics": [ "morie_svm_kernel_trick" ] }, { "page": "morie_sync_rng", "title": "Synchronised RNG seeded reproducibly for cross-language workflows", "topics": [ "morie_sync_rng" ] }, { "page": "morie_synth_corrections_uof", "title": "Build a synthetic Corrections-UoF data.frame for testing.", "topics": [ "morie_synth_corrections_uof" ] }, { "page": "morie_synth_otis", "title": "Build a synthetic OTIS data.frame for a given publication id.", "topics": [ "morie_synth_otis" ] }, { "page": "morie_synth_otis_all", "title": "Build the full 29-dataset OTIS synthetic list.", "topics": [ "morie_synth_otis_all" ] }, { "page": "morie_terry_hoeffding_test", "title": "Terry-Hoeffding (Fisher-Yates) two-sample normal-scores test (Gibbons Ch 8.3.1)", "topics": [ "morie_terry_hoeffding_test" ] }, { "page": "morie_tgarch_model", "title": "GJR-GARCH(1,1) threshold GARCH", "topics": [ "morie_tgarch_model" ] }, { "page": "morie_threshold_autoregression", "title": "Two-regime self-exciting threshold autoregressive (SETAR) model", "topics": [ "morie_threshold_autoregression" ] }, { "page": "morie_to_hood_crosswalk", "title": "Load the bundled BIDIRECTIONAL 158 <-> 140 neighbourhood crosswalk", "topics": [ "morie_to_hood_crosswalk" ] }, { "page": "morie_to_neighbourhoods", "title": "Load a Toronto neighbourhood polygon layer", "topics": [ "morie_to_neighbourhoods" ] }, { "page": "morie_tolerance_limits", "title": "Distribution-free (Wilks) tolerance limits", "topics": [ "morie_tolerance_limits" ] }, { "page": "morie_toronto_neighbourhoods", "title": "Toronto neighbourhood boundary versions", "topics": [ "morie_toronto_neighbourhoods" ] }, { "page": "morie_tps_add_hood_140_from_158", "title": "Add an equivalent HOOD_140 column to a HOOD_158-keyed data.frame", "topics": [ "morie_tps_add_hood_140_from_158" ] }, { "page": "morie_tps_add_hood_158_from_140", "title": "Add an equivalent HOOD_158 column to a HOOD_140-keyed data.frame", "topics": [ "morie_tps_add_hood_158_from_140" ] }, { "page": "morie_tps_aggregate_158_to_140", "title": "Aggregate per-158 counts to per-140 counts (EXACT for pure cake-cuts)", "topics": [ "morie_tps_aggregate_158_to_140" ] }, { "page": "morie_tps_analyze", "title": "RichResult-emitting analyses for the 13 TPS crime datasets", "topics": [ "morie_tps_analyze" ] }, { "page": "morie_tps_analyze_all", "title": "Run the full TPS analysis bundle across many TPS data.frames", "topics": [ "morie_tps_analyze_all" ] }, { "page": "morie_tps_analyze_assault", "title": "Convenience alias: full TPS bundle on the Assault dataset.", "topics": [ "morie_tps_analyze_assault", "morie_tps_analyze_autotheft", "morie_tps_analyze_bicycletheft", "morie_tps_analyze_breakandenter", "morie_tps_analyze_communitysafetyindicators", "morie_tps_analyze_hatecrimes", "morie_tps_analyze_homicides", "morie_tps_analyze_intimatepartnerandfamilyviolence", "morie_tps_analyze_neighbourhoodcrimerates", "morie_tps_analyze_robbery", "morie_tps_analyze_shootingandfirearmdiscarges", "morie_tps_analyze_theftfrommovingvehicle", "morie_tps_analyze_theftover" ] }, { "page": "morie_tps_analyze_csi_from_dataframes", "title": "Toronto CSI per-year + per-ward from a named list of TPS data.frames", "topics": [ "morie_tps_analyze_csi_from_dataframes" ] }, { "page": "morie_tps_analyze_one", "title": "Run the standard TPS analysis bundle on one data.frame", "topics": [ "morie_tps_analyze_one" ] }, { "page": "morie_tps_arima_forecast", "title": "ARIMA(1,1,1) monthly-count forecast", "topics": [ "morie_tps_arima_forecast" ] }, { "page": "morie_tps_assert_hood_version", "title": "Assert the HOOD_* schema version of a TPS data.frame", "topics": [ "morie_tps_assert_hood_version" ] }, { "page": "morie_tps_available_formats", "title": "List of formats this build can actually load.", "topics": [ "morie_tps_available_formats" ] }, { "page": "morie_tps_bivariate_moran", "title": "Bivariate Moran's I between two attributes at the same polygons", "topics": [ "morie_tps_bivariate_moran" ] }, { "page": "morie_tps_bivariate_morans_i", "title": "Bivariate Moran's I between two TPS categories", "topics": [ "morie_tps_bivariate_morans_i" ] }, { "page": "morie_tps_category_correlation_matrix", "title": "Pearson correlation across TPS categories' per-hood counts", "topics": [ "morie_tps_category_correlation_matrix" ] }, { "page": "morie_tps_changepoint_detection", "title": "Pettitt-style change-point on yearly incident counts", "topics": [ "morie_tps_changepoint_detection" ] }, { "page": "morie_tps_compare_hawkes_kernels", "title": "Compare Hawkes models across kernel x baseline combinations", "topics": [ "morie_tps_compare_hawkes_kernels" ] }, { "page": "morie_tps_composite_index", "title": "Composite per-neighbourhood crime-risk index across TPS categories", "topics": [ "morie_tps_composite_index" ] }, { "page": "morie_tps_crime_compare", "title": "Compare counts and trends across multiple TPS categories", "topics": [ "morie_tps_crime_compare" ] }, { "page": "morie_tps_criminal_network_graph", "title": "Premise x neighbourhood co-occurrence network", "topics": [ "morie_tps_criminal_network_graph" ] }, { "page": "MORIE_TPS_CSI_CATEGORIES", "title": "Canonical CSI category names (the 9 TPS open-data feeds).", "topics": [ "MORIE_TPS_CSI_CATEGORIES" ] }, { "page": "morie_tps_csi_per_neighbourhood", "title": "CSI per neighbourhood (HOOD_158)", "topics": [ "morie_tps_csi_per_neighbourhood" ] }, { "page": "morie_tps_csi_per_year", "title": "Toronto CSI per fiscal year from per-category counts", "topics": [ "morie_tps_csi_per_year" ] }, { "page": "morie_tps_csi_weight", "title": "Return the CSI weight for a TPS open-data category.", "topics": [ "morie_tps_csi_weight" ] }, { "page": "morie_tps_data_dir", "title": "Default project data directory for TPS open data.", "topics": [ "morie_tps_data_dir" ] }, { "page": "morie_tps_dbscan_clusters", "title": "DBSCAN density clusters on lat/long", "topics": [ "morie_tps_dbscan_clusters" ] }, { "page": "morie_tps_disaggregate_140_to_158", "title": "Disaggregate per-140 counts to per-158 counts (uniform-density)", "topics": [ "morie_tps_disaggregate_140_to_158" ] }, { "page": "morie_tps_district_for_centroid", "title": "Return the pre-1998 borough name for a (lat, lon) centroid", "topics": [ "morie_tps_district_for_centroid" ] }, { "page": "morie_tps_fetch_category", "title": "Fetch one TPS category as a CSV, paging until exhausted.", "topics": [ "morie_tps_fetch_category" ] }, { "page": "morie_tps_fetch_dataframe", "title": "Fetch a TPS category and return it as a 'data.frame'.", "topics": [ "morie_tps_fetch_dataframe" ] }, { "page": "morie_tps_fokker_planck_grid", "title": "1-D Fokker-Planck density evolution under OU drift+diffusion", "topics": [ "morie_tps_fokker_planck_grid" ] }, { "page": "morie_tps_getis_ord_g_star", "title": "Local Getis-Ord Gi* statistic per neighbourhood", "topics": [ "morie_tps_getis_ord_g_star" ] }, { "page": "morie_tps_gini_concentration", "title": "Gini coefficient of a numeric vector", "topics": [ "morie_tps_gini_concentration" ] }, { "page": "morie_tps_hawkes_advanced", "title": "Non-stationary Hawkes with non-exponential kernels (R port)", "topics": [ "morie_tps_hawkes_advanced" ] }, { "page": "morie_tps_hawkes_advanced_fit", "title": "Fit a single (kernel, baseline) Hawkes specification", "topics": [ "morie_tps_hawkes_advanced_fit" ] }, { "page": "morie_tps_hawkes_markovian_vs_nonmarkovian", "title": "Focused 2x2 Markovian vs non-Markovian Hawkes comparison", "topics": [ "morie_tps_hawkes_markovian_vs_nonmarkovian" ] }, { "page": "morie_tps_hawkes_temporal_fit", "title": "Temporal exponential-kernel Hawkes fit", "topics": [ "morie_tps_hawkes_temporal_fit" ] }, { "page": "morie_tps_inspection_game_phase", "title": "Helbing-Szolnoki inspection-game phase diagram", "topics": [ "morie_tps_inspection_game_phase" ] }, { "page": "morie_tps_kde_density", "title": "2-D kernel density estimate of geocoded incidents", "topics": [ "morie_tps_kde_density" ] }, { "page": "morie_tps_langevin_simulate", "title": "Euler-Maruyama Ornstein-Uhlenbeck simulation", "topics": [ "morie_tps_langevin_simulate" ] }, { "page": "morie_tps_layer_urls", "title": "TPS ArcGIS layer URLs known to MORIE", "topics": [ "MORIE_TPS_LAYER_URLS", "morie_tps_layer_urls" ] }, { "page": "morie_tps_levy_flight_alpha", "title": "Levy-flight tail exponent on consecutive-incident steps", "topics": [ "morie_tps_levy_flight_alpha" ] }, { "page": "morie_tps_list_categories", "title": "List TPS categories known to the fetcher.", "topics": [ "morie_tps_list_categories" ] }, { "page": "morie_tps_list_datasets", "title": "List all TPS datasets as a 'data.frame'.", "topics": [ "morie_tps_list_datasets" ] }, { "page": "morie_tps_list_formats", "title": "Map TPS format name -> path of the file that would be loaded.", "topics": [ "morie_tps_list_formats" ] }, { "page": "morie_tps_load", "title": "Load TPS dataset 'name' in the given 'format'.", "topics": [ "morie_tps_load" ] }, { "page": "morie_tps_load_dataset", "title": "Load one TPS dataset by category name (CSV thin path).", "topics": [ "morie_tps_load_dataset" ] }, { "page": "morie_tps_local_morans_i", "title": "LISA - local Moran's Ii per neighbourhood", "topics": [ "morie_tps_local_morans_i" ] }, { "page": "morie_tps_lotka_volterra_police_crime", "title": "Lotka-Volterra predator-prey on yearly crime counts", "topics": [ "morie_tps_lotka_volterra_police_crime" ] }, { "page": "morie_tps_moran_sweep_heatmap", "title": "Sweep polygon Moran's I across (category x year)", "topics": [ "morie_tps_moran_sweep_heatmap" ] }, { "page": "morie_tps_morans_i_neighbourhood", "title": "Global Moran's I on neighbourhood-level incident counts", "topics": [ "morie_tps_morans_i_neighbourhood" ] }, { "page": "morie_tps_neighbourhood_concentration", "title": "How concentrated is crime across Toronto's 158 neighbourhoods?", "topics": [ "morie_tps_neighbourhood_concentration" ] }, { "page": "morie_tps_offence_summary", "title": "Offence-distribution rollup for a TPS crime data.frame", "topics": [ "morie_tps_offence_summary" ] }, { "page": "morie_tps_polygon_morans_i", "title": "Polygon-aware Moran's I on a value column", "topics": [ "morie_tps_polygon_morans_i" ] }, { "page": "morie_tps_pretty_label", "title": "Convert a SQL-style column name to a prose label", "topics": [ "morie_tps_pretty_label" ] }, { "page": "morie_tps_project_xy", "title": "Project (lat, lon) to rotated planar kilometres", "topics": [ "morie_tps_project_xy" ] }, { "page": "morie_tps_psdp_layers", "title": "List the TPS PSDP layers wrapped by morie", "topics": [ "morie_tps_psdp_layers" ] }, { "page": "MORIE_TPS_REGISTRY", "title": "Registry of TPS open-data categories.", "topics": [ "MORIE_TPS_REGISTRY" ] }, { "page": "morie_tps_render", "title": "Toronto Police Service map rendering (R-side)", "topics": [ "morie_tps_render" ] }, { "page": "morie_tps_render_choropleth", "title": "Polygon choropleth map for Toronto (158 wards)", "topics": [ "morie_tps_render_choropleth" ] }, { "page": "morie_tps_render_dbscan", "title": "DBSCAN cluster figure on TPS-projected points", "topics": [ "morie_tps_render_dbscan" ] }, { "page": "morie_tps_render_district_proportional", "title": "District-level proportional-symbol map", "topics": [ "morie_tps_render_district_proportional" ] }, { "page": "morie_tps_render_points", "title": "Render a TPS point-pattern map (incident dots, optional DBSCAN)", "topics": [ "morie_tps_render_points" ] }, { "page": "morie_tps_render_quad", "title": "Four-panel composite of TPS rendering primitives", "topics": [ "morie_tps_render_quad" ] }, { "page": "morie_tps_render_satscan_panel", "title": "SaTScan-style spatial scan panel", "topics": [ "morie_tps_render_satscan_panel" ] }, { "page": "morie_tps_render_yearly_grid", "title": "Small-multiples panel of per-year TPS choropleths", "topics": [ "morie_tps_render_yearly_grid" ] }, { "page": "morie_tps_resolve_hood_col", "title": "Resolve which HOOD_* column to use on a TPS crime data.frame", "topics": [ "morie_tps_resolve_hood_col" ] }, { "page": "morie_tps_ripley_k", "title": "Ripley's K function at multiple radii", "topics": [ "morie_tps_ripley_k" ] }, { "page": "morie_tps_sarima_forecast", "title": "Seasonal ARIMA forecast on monthly incident counts", "topics": [ "morie_tps_sarima_forecast" ] }, { "page": "morie_tps_sdb_reaction_diffusion", "title": "Short-D'Orsogna-Brantingham 2008 hot-spot PDE", "topics": [ "morie_tps_sdb_reaction_diffusion" ] }, { "page": "morie_tps_sdb_turing_demo", "title": "Canonical Short-D'Orsogna-Brantingham Turing-pattern demo", "topics": [ "morie_tps_sdb_turing_demo" ] }, { "page": "morie_tps_seasonal_pattern", "title": "Seasonal / cyclic incident-time patterns", "topics": [ "morie_tps_seasonal_pattern" ] }, { "page": "morie_tps_spatial_summary", "title": "Spatial rollup for a TPS crime data.frame", "topics": [ "morie_tps_spatial_summary" ] }, { "page": "morie_tps_statphysics", "title": "Statistical physics of crime for TPS data", "topics": [ "morie_tps_statphysics" ] }, { "page": "morie_tps_statphysics_analyze_all", "title": "Run all four statistical-physics analyses on a list of categories", "topics": [ "morie_tps_statphysics_analyze_all" ] }, { "page": "morie_tps_stochastic", "title": "Stochastic-physics-of-crime analyses for TPS data", "topics": [ "morie_tps_stochastic" ] }, { "page": "MORIE_TPS_SUPPORTED_FORMATS", "title": "Format names that 'morie_tps_load()' knows how to dispatch.", "topics": [ "MORIE_TPS_SUPPORTED_FORMATS" ] }, { "page": "morie_tps_temporal", "title": "Temporal analyses for TPS crime data", "topics": [ "morie_tps_temporal" ] }, { "page": "morie_tps_temporal_summary", "title": "Temporal rollup for a TPS crime data.frame", "topics": [ "morie_tps_temporal_summary" ] }, { "page": "MORIE_TPS_TORONTO_POPULATION_BY_YEAR", "title": "Toronto reference population by fiscal year (StatsCan 17-10-0009-01).", "topics": [ "MORIE_TPS_TORONTO_POPULATION_BY_YEAR" ] }, { "page": "MORIE_TPS_TOTAL_CSI_WEIGHTS", "title": "Total-CSI weights for the 9 TPS open-data categories.", "topics": [ "MORIE_TPS_TOTAL_CSI_WEIGHTS" ] }, { "page": "morie_tps_urban_scaling_beta", "title": "Bettencourt urban-scaling exponent across the 158 Toronto wards", "topics": [ "morie_tps_urban_scaling_beta" ] }, { "page": "morie_tps_use_of_force", "title": "TPS Use-of-Force rate + type distribution", "topics": [ "morie_tpsuof", "morie_tps_use_of_force" ] }, { "page": "MORIE_TPS_VIOLENT_CSI_WEIGHTS", "title": "Violent-CSI weights for the 9 TPS open-data categories.", "topics": [ "MORIE_TPS_VIOLENT_CSI_WEIGHTS" ] }, { "page": "morie_tps_year_over_year_trend", "title": "Year-over-year linear trend on incident counts", "topics": [ "morie_tps_year_over_year_trend" ] }, { "page": "morie_tps_year_to_hood_version", "title": "Recommended HOOD_* schema version for a given OCC_YEAR", "topics": [ "morie_tps_year_to_hood_version" ] }, { "page": "morie_tps_yoy_panel", "title": "Side-by-side year-over-year panel across TPS categories", "topics": [ "morie_tps_yoy_panel" ] }, { "page": "morie_transformer_genomic", "title": "Transformer (1-head self-attention) genomic predictor (base R)", "topics": [ "morie_transformer_genomic" ] }, { "page": "morie_tsne_reduction", "title": "t-SNE for non-linear dimension reduction (R parity)", "topics": [ "morie_tsne_reduction" ] }, { "page": "morie_two_sample_coverage", "title": "Two-sample placement coverage (Gibbons Ch 2.11.2)", "topics": [ "morie_two_sample_coverage" ] }, { "page": "morie_two_sample_t_test", "title": "Two-sample t-test with tidy output", "topics": [ "morie_two_sample_t_test" ] }, { "page": "morie_unobserved_components", "title": "Unobserved-components decomposition (trend + seasonal + irregular)", "topics": [ "morie_unobserved_components" ] }, { "page": "morie_userguide", "title": "Get path to an MORIE userguide", "topics": [ "morie_userguide" ] }, { "page": "morie_validate_cpads_data", "title": "Validate a CPADS analysis data frame", "topics": [ "morie_validate_cpads_data" ] }, { "page": "morie_validate_outputs_manifest", "title": "Validate outputs manifest structure", "topics": [ "morie_validate_outputs_manifest" ] }, { "page": "morie_van_der_waerden_test", "title": "Van der Waerden two-sample normal-scores location test (Gibbons Ch 8.3.2)", "topics": [ "morie_van_der_waerden_test" ] }, { "page": "morie_vecm", "title": "Vector error-correction model (VECM)", "topics": [ "morie_vecm" ] }, { "page": "morie_verify_statistical_output", "title": "Verify that a serialised statistical output meets minimum quality gates", "topics": [ "morie_verify_statistical_output" ] }, { "page": "morie_vertex_access_token", "title": "Fetch and cache a Google Cloud access token via gcloud", "topics": [ "morie_vertex_access_token" ] }, { "page": "morie_vertex_ask_gemini", "title": "Send a single-turn prompt to Gemini via Vertex AI", "topics": [ "morie_vertex_ask_gemini" ] }, { "page": "morie_vertex_health_check", "title": "Tiny smoke test for the Vertex AI client", "topics": [ "morie_vertex_health_check" ] }, { "page": "morie_vertex_resolve_config", "title": "Resolve Vertex AI configuration from environment variables", "topics": [ "morie_vertex_resolve_config" ] }, { "page": "morie_vpd_download_instructions", "title": "Print step-by-step VPD GeoDASH download instructions", "topics": [ "morie_vpd_download_instructions" ] }, { "page": "morie_wavelet_time_series", "title": "Discrete wavelet decomposition for a time series", "topics": [ "morie_wavelet_time_series" ] }, { "page": "morie_weights_bootstrap", "title": "Bootstrap replicate weights (Rao-Wu rescaling within strata).", "topics": [ "morie_weights_bootstrap" ] }, { "page": "morie_weights_brr", "title": "Balanced Repeated Replication (BRR) weights.", "topics": [ "morie_weights_brr" ] }, { "page": "morie_weights_calibrate_to_totals", "title": "Dispatch helper - calibrate to totals via \"raking\" or \"greg\".", "topics": [ "morie_weights_calibrate_to_totals" ] }, { "page": "morie_weights_combined", "title": "Combined design x nonresponse x post-strat (x trim) pipeline.", "topics": [ "morie_weights_combined" ] }, { "page": "morie_weights_deff", "title": "Kish design effect (n / ESS).", "topics": [ "morie_weights_deff" ] }, { "page": "morie_weights_design", "title": "Design weights from inclusion probabilities.", "topics": [ "morie_weights_design" ] }, { "page": "morie_weights_detect_extreme", "title": "Detect extreme weights at +/- k * IQR or by absolute percentile.", "topics": [ "morie_weights_detect_extreme" ] }, { "page": "morie_weights_diagnostics", "title": "Comprehensive weight diagnostics.", "topics": [ "morie_weights_diagnostics" ] }, { "page": "morie_weights_ess", "title": "Kish effective sample size: (sum w_i)^2 / sum w_i^2.", "topics": [ "morie_weights_ess" ] }, { "page": "morie_weights_fay_brr", "title": "Fay's BRR weights with perturbation coefficient 'fay_coefficient' in [0,1).", "topics": [ "morie_weights_fay_brr" ] }, { "page": "morie_weights_greg", "title": "Generalised regression (GREG) calibration.", "topics": [ "morie_weights_greg" ] }, { "page": "morie_weights_jackknife", "title": "Jackknife replicate weights (JK1 delete-1 or JKn stratified delete-n).", "topics": [ "morie_weights_jackknife" ] }, { "page": "morie_weights_multiframe", "title": "Multi-frame (dual-frame) survey weights (Hartley compositing).", "topics": [ "morie_weights_multiframe" ] }, { "page": "morie_weights_nonresponse", "title": "Non-response adjustment within cells.", "topics": [ "morie_weights_nonresponse" ] }, { "page": "morie_weights_normalize", "title": "Normalise weights so they sum to n (sample) or N (population).", "topics": [ "morie_weights_normalize" ] }, { "page": "morie_weights_poststratify", "title": "Post-stratification weight adjustment.", "topics": [ "morie_weights_poststratify" ] }, { "page": "morie_weights_propensity_nonresponse", "title": "Propensity-score non-response weights (logistic).", "topics": [ "morie_weights_propensity_nonresponse" ] }, { "page": "morie_weights_rake", "title": "Raking calibration (iterative proportional fitting).", "topics": [ "morie_weights_rake" ] }, { "page": "morie_weights_replicate_variance", "title": "Variance estimation from replicate estimates.", "topics": [ "morie_weights_replicate_variance" ] }, { "page": "morie_weights_sdr", "title": "Successive Difference Replication (SDR) weights.", "topics": [ "morie_weights_sdr" ] }, { "page": "morie_weights_smooth", "title": "Smooth survey weights via shrinkage toward the mean (or log-mean).", "topics": [ "morie_weights_smooth" ] }, { "page": "morie_weights_trim", "title": "Trim extreme weights at percentile cutpoints.", "topics": [ "morie_weights_trim" ] }, { "page": "morie_wilcoxon_power", "title": "Monte-Carlo power of the Wilcoxon signed-rank test (Gibbons Ch 5.7.3)", "topics": [ "morie_wilcoxon_power" ] }, { "page": "morie_wilcoxon_signed_rank_test", "title": "Wilcoxon signed-rank test (paired)", "topics": [ "morie_wilcoxon_signed_rank_test" ] }, { "page": "morie_write_audit_markdown", "title": "Write a Markdown audit report.", "topics": [ "morie_write_audit_markdown" ] }, { "page": "morie_write_synthetic_data", "title": "Write synthetic epidemiology-style data to CSV", "topics": [ "morie_write_synthetic_data" ] }, { "page": "morie_xgboost_objective", "title": "XGBoost regularized objective (R parity)", "topics": [ "morie_xgboost_objective" ] }, { "page": "mrm_anova_bonferroni", "title": "One-way ANOVA with pairwise Bonferroni-adjusted t-tests", "topics": [ "mrm_anova_bonferroni" ] }, { "page": "mrm_anova_oneway", "title": "One-way ANOVA + Tukey HSD post-hoc", "topics": [ "mrm_anova_oneway" ] }, { "page": "mrm_anova_power", "title": "Power of one-way ANOVA given Cohen's f", "topics": [ "mrm_anova_power" ] }, { "page": "mrm_arsau", "title": "Per-record-type ARSAU analysis pipelines (R-side)", "topics": [ "mrm_arsau" ] }, { "page": "mrm_assumptions_check", "title": "Composite Rubin-style identifiability assumption check", "topics": [ "mrm_assumptions_check" ] }, { "page": "mrm_causal_design", "title": "Designed-experiment convenience wrapper around the morie causal estimator family", "topics": [ "mrm_causal_design" ] }, { "page": "mrm_check_balancing", "title": "Composite balance verdict using the Imbens-Rubin %SMD criterion", "topics": [ "mrm_check_balancing" ] }, { "page": "mrm_check_overlap", "title": "Propensity-score support overlap diagnostic (Cole-Hernan 2008)", "topics": [ "mrm_check_overlap" ] }, { "page": "mrm_classify_mandela", "title": "Mandela Rules classifier for solitary-confinement placements", "topics": [ "mrm_classify_mandela" ] }, { "page": "mrm_clt_demo", "title": "Central Limit Theorem demonstrator", "topics": [ "mrm_clt_demo" ] }, { "page": "mrm_design", "title": "Experimental-design callables (designexptr-inspired)", "topics": [ "mrm_design" ] }, { "page": "mrm_diagnostics", "title": "Causal-inference diagnostics (R parity)", "topics": [ "mrm_diagnostics" ] }, { "page": "mrm_doe", "title": "Design-of-Experiments toolkit (R parity)", "topics": [ "mrm_doe" ] }, { "page": "mrm_factorial_2k", "title": "2^k factorial-design analysis with main effects + interactions", "topics": [ "mrm_factorial_2k" ] }, { "page": "mrm_fractional_factorial", "title": "Fractional 2^(k-p) factorial: main effects + alias structure", "topics": [ "mrm_fractional_factorial" ] }, { "page": "mrm_gentrification", "title": "Baseline-conditional gentrification coding (MRM primitive)", "topics": [ "mrm_gentrification" ] }, { "page": "mrm_gentrification_panel", "title": "Construct a baseline-conditional 3-level gentrification factor", "topics": [ "mrm_gentrification_panel" ] }, { "page": "mrm_graeco_latin", "title": "Graeco-Latin square four-way ANOVA (row, col, Latin, Greek)", "topics": [ "mrm_graeco_latin" ] }, { "page": "mrm_kulldorff", "title": "Kulldorff space-time scan statistic on TPS event data", "topics": [ "mrm_kulldorff" ] }, { "page": "mrm_latin_square", "title": "Latin-square three-way ANOVA (row, col, treatment)", "topics": [ "mrm_latin_square" ] }, { "page": "mrm_lisa", "title": "LISA (Local Indicators of Spatial Association) on polygon-level crime data + per-year polygon Moran's I time series", "topics": [ "mrm_lisa" ] }, { "page": "mrm_mathstats", "title": "Mathematical-statistics / simulation / computation toolkit (R parity)", "topics": [ "mrm_mathstats" ] }, { "page": "mrm_mc_power", "title": "Empirical Monte-Carlo power", "topics": [ "mrm_mc_power" ] }, { "page": "mrm_median_causal_effect", "title": "Median causal effect via 1:1 nearest-neighbour PS matching", "topics": [ "mrm_median_causal_effect" ] }, { "page": "mrm_morans_i", "title": "Moran's I statistic for residual spatial autocorrelation", "topics": [ "mrm_morans_i" ] }, { "page": "mrm_oneprop_test", "title": "One-proportion test (binomial exact + Wald approximation)", "topics": [ "mrm_oneprop_test" ] }, { "page": "mrm_otis", "title": "MRM-framework analyses on Ontario OTIS data", "topics": [ "mrm_otis" ] }, { "page": "mrm_otis_mandela_spectrum", "title": "Mandela Rules apples-to-apples spectrum on OTIS b01", "topics": [ "mrm_otis_mandela_spectrum" ] }, { "page": "mrm_otis_mortification_cooccurrence", "title": "Pairwise Cramer's V of OTIS b01 alert columns (mortification proxy)", "topics": [ "mrm_otis_mortification_cooccurrence" ] }, { "page": "mrm_otis_placement_concentration", "title": "Per-individual segregation-placement-count concentration on OTIS b09", "topics": [ "mrm_otis_placement_concentration" ] }, { "page": "mrm_otis_region_locality", "title": "OTIS b01 region locality: chi-square + diagonal-share", "topics": [ "mrm_otis_region_locality" ] }, { "page": "mrm_otis_seg_duration_km", "title": "Kaplan-Meier survival on OTIS b01 segregation-placement durations", "topics": [ "mrm_otis_seg_duration_km" ] }, { "page": "mrm_perm_block", "title": "Block-permutation test for treatment effect", "topics": [ "mrm_perm_block" ] }, { "page": "mrm_pit", "title": "Probability Integral Transform (PIT)", "topics": [ "mrm_pit" ] }, { "page": "mrm_primitives_ordinal", "title": "Threshold-specific ordinal-logit primitive (MRM)", "topics": [ "mrm_primitives_ordinal" ] }, { "page": "mrm_qq_plot", "title": "Q-Q plot coordinates against a reference distribution", "topics": [ "mrm_qq_plot" ] }, { "page": "mrm_random_latin", "title": "Generate a random k x k Latin square", "topics": [ "mrm_random_latin" ] }, { "page": "mrm_rcbd", "title": "Randomised complete block design (RCBD) two-way ANOVA", "topics": [ "mrm_rcbd" ] }, { "page": "mrm_response_surface", "title": "Second-order response-surface fit (Box-Wilson 1951)", "topics": [ "mrm_response_surface" ] }, { "page": "mrm_samples", "title": "Bundled reference data samples and dataset fetchers", "topics": [ "mrm_samples" ] }, { "page": "mrm_siu", "title": "MRM-framework analyses on Ontario SIU (Special Investigations Unit) data", "topics": [ "mrm_siu" ] }, { "page": "mrm_siu_case_to_decision_km", "title": "KM survival of SIU case-to-decision gap per police service", "topics": [ "mrm_siu_case_to_decision_km" ] }, { "page": "mrm_siu_outcome_classifier", "title": "Tabulate SIU Director's-decision outcomes", "topics": [ "mrm_siu_outcome_classifier" ] }, { "page": "mrm_siu_per_service_rate", "title": "Per-police-service SIU case-rate summary", "topics": [ "mrm_siu_per_service_rate" ] }, { "page": "mrm_spatial_spillover", "title": "Spatial Durbin / SAR direct-indirect-total decomposition (MRM primitive)", "topics": [ "mrm_spatial_spillover" ] }, { "page": "mrm_spatial_spillover_decomposition", "title": "SDM direct / indirect / total decomposition", "topics": [ "mrm_spatial_spillover_decomposition" ] }, { "page": "mrm_standardised_difference", "title": "Imbens-Rubin standardised %SMD per covariate", "topics": [ "mrm_standardised_difference" ] }, { "page": "mrm_synthetic_area_exposure", "title": "Compute the synthetic exposure offset for each area", "topics": [ "mrm_synthetic_area_exposure" ] }, { "page": "mrm_synthetic_exposure", "title": "Synthetic small-area-estimated exposure offset (MRM primitive)", "topics": [ "mrm_synthetic_exposure" ] }, { "page": "mrm_threshold_coefficient", "title": "Extract coefficient(s) for one covariate across all thresholds", "topics": [ "mrm_threshold_coefficient" ] }, { "page": "mrm_threshold_specific_ordinal", "title": "Fit a threshold-specific cumulative-logit ordinal regression", "topics": [ "mrm_threshold_specific_ordinal" ] }, { "page": "mrm_tps", "title": "MRM-framework analyses on Toronto Police Service (TPS) open data", "topics": [ "mrm_tps" ] }, { "page": "mrm_tps_kulldorff_scan", "title": "Run a 3-d (lat, lon, time) Kulldorff scan with MC inference", "topics": [ "mrm_tps_kulldorff_scan" ] }, { "page": "mrm_tps_levy_scaling", "title": "Levy-flight Hill-MLE exponent on TPS inter-incident step lengths", "topics": [ "mrm_tps_levy_scaling" ] }, { "page": "mrm_tps_lisa", "title": "Local Moran's I per polygon + quadrant + 999-permutation significance", "topics": [ "mrm_tps_lisa" ] }, { "page": "mrm_tps_load_hawkes_refit", "title": "Load the precomputed per-category TPS Hawkes refit manifest", "topics": [ "mrm_tps_load_hawkes_refit" ] }, { "page": "mrm_tps_moran_clustering", "title": "Global Moran's I + DBSCAN summary on TPS lat/long event data", "topics": [ "mrm_tps_moran_clustering" ] }, { "page": "mrm_tps_neighbourhood_recurrence_km", "title": "Kaplan-Meier inter-event recurrence on TPS by neighbourhood", "topics": [ "mrm_tps_neighbourhood_recurrence_km" ] }, { "page": "mrm_tps_polygon_moran_per_year", "title": "Per-year global Moran's I time series across a polygon surface", "topics": [ "mrm_tps_polygon_moran_per_year" ] }, { "page": "mrm_two_treatment_test", "title": "Two-treatment outcome comparison with three assumption regimes", "topics": [ "mrm_two_treatment_test" ] }, { "page": "mrm_twoprop_test", "title": "Two-proportion test (chi-square + Fisher exact + Wald)", "topics": [ "mrm_twoprop_test" ] }, { "page": "mrm_uof", "title": "Generic Multilevel Reconciliation Methodology (MRM) Use-of-Force callables", "topics": [ "mrm_uof" ] }, { "page": "mrm_uof_data_quality_audit", "title": "Schema, null, and suspect-value audit", "topics": [ "mrm_uof_data_quality_audit" ] }, { "page": "mrm_uof_demographic_disparity", "title": "Demographic disparity in outcome rates with risk-ratio CIs", "topics": [ "mrm_uof_demographic_disparity" ] }, { "page": "mrm_uof_force_concentration", "title": "Concentration of UoF incidents across forces / services", "topics": [ "mrm_uof_force_concentration" ] }, { "page": "mrm_uof_region_locality", "title": "Region-at-time vs region-now locality contingency", "topics": [ "mrm_uof_region_locality" ] }, { "page": "mrm_uof_weapon_diversity", "title": "Weapon-by-force contingency test", "topics": [ "mrm_uof_weapon_diversity" ] }, { "page": "mrm_uof_yoy_change", "title": "Year-on-year change in incident counts", "topics": [ "mrm_uof_yoy_change" ] }, { "page": "mrm_var_test", "title": "Chi-square test for variance (Wilks 1962)", "topics": [ "mrm_var_test" ] }, { "page": "n_effective_tests", "title": "Effective number of independent tests from a correlation matrix", "topics": [ "n_effective_tests" ] }, { "page": "n_stat_commands", "title": "Total number of registered commands (excluding aliases)", "topics": [ "n_stat_commands" ] }, { "page": "nested_cross_validate", "title": "Nested cross-validation with inner-loop grid search", "topics": [ "nested_cross_validate" ] }, { "page": "normality_suite", "title": "Run a suite of normality tests", "topics": [ "normality_suite" ] }, { "page": "number_needed_to_harm", "title": "Number needed to harm (NNH) — sign-reversed NNT", "topics": [ "number_needed_to_harm" ] }, { "page": "number_needed_to_treat", "title": "Number needed to treat (NNT) = 1 / |RD|", "topics": [ "number_needed_to_treat" ] }, { "page": "nw_regression", "title": "Nadaraya-Watson kernel regression", "topics": [ "nw_regression" ] }, { "page": "odds_ratio", "title": "Odds ratio for a 2x2 table [[a, b], [c, d]]", "topics": [ "odds_ratio" ] }, { "page": "odds_ratio_table", "title": "Odds-ratio table from a fitted logistic GLM", "topics": [ "odds_ratio_table" ] }, { "page": "omega_squared", "title": "Omega-squared — less biased than eta-squared", "topics": [ "omega_squared" ] }, { "page": "omitted_variable_bias", "title": "Omitted-variable bias analysis (sensemakr framework)", "topics": [ "omitted_variable_bias" ] }, { "page": "one_proportion_ztest", "title": "One-sample z-test for a proportion", "topics": [ "one_proportion_ztest" ] }, { "page": "one_sample_ttest", "title": "One-sample Student's t-test", "topics": [ "one_sample_ttest" ] }, { "page": "one_way_anova", "title": "One-way between-subjects ANOVA", "topics": [ "one_way_anova" ] }, { "page": "or_to_d", "title": "Convert odds ratio to Cohen's d (Hasselblad & Hedges, 1995)", "topics": [ "or_to_d" ] }, { "page": "or_to_r", "title": "Convert OR to Pearson r via d", "topics": [ "or_to_r" ] }, { "page": "paired_permutation_test", "title": "Paired permutation test (sign-flipping)", "topics": [ "paired_permutation_test" ] }, { "page": "paired_ttest", "title": "Paired-sample t-test", "topics": [ "paired_ttest" ] }, { "page": "parametric_bootstrap", "title": "Parametric bootstrap", "topics": [ "parametric_bootstrap" ] }, { "page": "partial_correlation", "title": "Partial Pearson correlation controlling for covariates", "topics": [ "partial_correlation" ] }, { "page": "partial_eta_squared", "title": "Partial eta-squared", "topics": [ "partial_eta_squared" ] }, { 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