| Subsetting method for climasus_df | [.climasus_df |
| Column extraction for climasus_df | [[.climasus_df |
| Column assignment for climasus_df | $<-.climasus_df |
| Coerce climasus_df to plain data.frame (strips metadata) | as.data.frame.climasus_df |
| Extract coefficients from a climasus_dlnm model | coef.climasus_dlnm |
| Extract pooled coefficients from a climasus_metaregression object | coef.climasus_metaregression |
| Extract pooled coefficients from a climasus_pool object | coef.climasus_pool |
| Extract VI scores as a named numeric vector | coef.climasus_vi |
| Return daily rows where at least one coldwave method is active | cw_active_days |
| Count coldwave events by year, station, and method | cw_count_by_year |
| Extract coldwave events table from a climasus_cw result | cw_get_events |
| Return daily rows where at least one heatwave method is active | hw_active_days |
| Count heatwave events by year, station, and method | hw_count_by_year |
| Extract heatwave events table from a climasus_hw result | hw_get_events |
| Generate predictions from a climasus_ml model on new data | predict.climasus_ml |
| Print a climasus_af object | print.climasus_af |
| Print a climasus_burden object | print.climasus_burden |
| Print a climasus_casecrossover object | print.climasus_casecrossover |
| Print method for climasus_df | print.climasus_df |
| Print a climasus_dlnm model | print.climasus_dlnm |
| Print a climasus_excess object | print.climasus_excess |
| Print a climasus_its object | print.climasus_its |
| Print a climasus_metaregression object | print.climasus_metaregression |
| Print a climasus_ml object | print.climasus_ml |
| Print a climasus_pool object | print.climasus_pool |
| Print a climasus_sensitivity object | print.climasus_sensitivity |
| Print method for climasus_spacetime_bayes objects | print.climasus_spacetime_bayes |
| Print method for climasus_spacetime_exceedance objects | print.climasus_spacetime_exceedance |
| Print method for climasus_spacetime_pred objects | print.climasus_spacetime_pred |
| Print method for climasus_spatial_bayes objects | print.climasus_spatial_bayes |
| Print method for climasus_spatial_moran objects | print.climasus_spatial_moran |
| Print method for climasus_spatial_reg objects | print.climasus_spatial_reg |
| Print a climasus_spatial_scan object | print.climasus_spatial_scan |
| Print a climasus_swot object | print.climasus_swot |
| Print a climasus_ts_quality object | print.climasus_ts_quality |
| Print a climasus_vi object | print.climasus_vi |
| Print method for climasus_weights | print.climasus_weights |
| Row binding for climasus_df objects | rbind.climasus_df |
| Summarise a climasus_af object | summary.climasus_af |
| Summarise a climasus_burden object | summary.climasus_burden |
| Summarise a climasus_casecrossover object | summary.climasus_casecrossover |
| Summarise a climasus_dlnm model | summary.climasus_dlnm |
| Summarise a climasus_excess object | summary.climasus_excess |
| Summarise a climasus_its object | summary.climasus_its |
| Summarise a climasus_metaregression object | summary.climasus_metaregression |
| Summarise a climasus_ml object | summary.climasus_ml |
| Summarise a climasus_pool object | summary.climasus_pool |
| Summarise a climasus_sensitivity object | summary.climasus_sensitivity |
| Summary method for climasus_spacetime_bayes objects | summary.climasus_spacetime_bayes |
| Summary method for climasus_spacetime_exceedance objects | summary.climasus_spacetime_exceedance |
| Summary method for climasus_spacetime_pred objects | summary.climasus_spacetime_pred |
| Summary method for climasus_spatial_bayes objects | summary.climasus_spatial_bayes |
| Summary method for climasus_spatial_moran objects | summary.climasus_spatial_moran |
| Summary method for climasus_spatial_reg objects | summary.climasus_spatial_reg |
| Summarise a climasus_spatial_scan object | summary.climasus_spatial_scan |
| Summarise a climasus_swot object | summary.climasus_swot |
| Summarise a climasus_ts_quality object | summary.climasus_ts_quality |
| Summarise a climasus_vi object | summary.climasus_vi |
| Summary method for climasus_weights | summary.climasus_weights |
| Convert a climasus_df to an Arrow Table with embedded metadata | sus_as_arrow |
| Convert a climasus_df to a DuckDB lazy tbl with embedded metadata | sus_as_duckdb |
| Clear the Climasus4r cache | sus_cache_clear |
| Get cache information | sus_cache_info |
| Add Census Socioeconomic variables to Health Data | sus_census_join |
| Interactive Census Variables Explorer | sus_census_select |
| Launch the climasus4r AI Assistant | sus_chat |
| Integration of Climate and Health Data | sus_climate_aggregate |
| Climate Anomaly Computation vs. INMET Climatological Normals | sus_climate_anomaly |
| Detect coldwaves using multiple standard methodologies | sus_climate_compute_coldwaves |
| Detect heatwaves using multiple standard methodologies | sus_climate_compute_heatwaves |
| Compute Bioclimatic and Thermal Stress Indicators | sus_climate_compute_indicators |
| Compute Standardized Precipitation-Evapotranspiration Index (SPEI) | sus_climate_compute_spei |
| Compute Standardized Precipitation Index (SPI) | sus_climate_compute_spi |
| Fill gaps in INMET climate time series using XGBoost | sus_climate_fill_inmet |
| Import and Process INMET Meteorological Data | sus_climate_inmet |
| Download and Process INMET Climate Normals | sus_climate_normals |
| Browse the INMET Climate Normals Catalogue | sus_climate_normals_meta |
| Visualise Climate-Health Aggregate Data | sus_climate_plot_aggregate |
| Plot and Analyze Coldwave Events | sus_climate_plot_coldwaves |
| Visualise time-series gap-filling from sus_climate_fill() | sus_climate_plot_fill |
| Plot and Analyze Heatwave Events | sus_climate_plot_heatwaves |
| Import UNIPLU-BR: Unified Brazilian Rainfall Dataset | sus_climate_uniplu |
| Aggregate Health Data into Time Series | sus_data_aggregate |
| Interactive Disease Groups Explorer | sus_data_cid_select |
| Detect and correct character encoding issues | sus_data_clean_encoding |
| Create Derived Variables for Epidemiological Analysis | sus_data_create_variables |
| Export Processed Health Data with Metadata | sus_data_export |
| Filter SUS health data by ICD-10 codes or disease groups with multilingual support | sus_data_filter_cid |
| Filter Health Data by Demographic Variables | sus_data_filter_demographics |
| Import and preprocess data from DATASUS with intelligent caching | sus_data_import |
| Plot Municipal Map of Aggregated Health Data | sus_data_plot_aggregate_map |
| Time-Series Plot of Aggregated DATASUS Health Outcomes | sus_data_plot_aggregate_ts |
| Visualise Demographic Profiles from DATASUS Systems | sus_data_plot_demographics |
| Pipeline-aware data quality report for health data | sus_data_quality_report |
| Read Processed Health Data with Batch and Parallel Support | sus_data_read |
| Standardize SUS data column names and values | sus_data_standardize |
| Time-Series Quality Control for Daily Municipal Health Counts | sus_data_ts_quality |
| Import CHIRPS Rainfall Data for Brazilian Municipalities | sus_grid_chirps |
| Import ERA5-Land Daily Climate Data for Brazilian Municipalities | sus_grid_era5 |
| Import Fire Hotspot Data for Brazilian Municipalities | sus_grid_fires |
| Join Gridded Environmental Data to Health Data | sus_grid_join |
| Assign Kopppen-Geiger Climate Zones to Brazilian Municipalities | sus_grid_koppen |
| Import Palmer Drought Severity Index (PDSI) for Brazilian Municipalities | sus_grid_pdsi |
| Import CAMS Pollution Data for Brazilian Municipalities | sus_grid_pollution_cams |
| Import GHAP High-Resolution Pollution Data for Brazilian Municipalities | sus_grid_pollution_ghap |
| Import MERRA-2 Pollution Data for Brazilian Municipalities | sus_grid_pollution_merra2 |
| Import PRODES Deforestation Data from TerraBrasilis for Brazilian Municipalities | sus_grid_prodes |
| Import Soil Moisture Volatility Index (SMVI / Flash Drought) Data | sus_grid_smvi |
| Install Optional Dependencies for climasus4r | sus_install_deps |
| Manage climasus_df S3 Class Metadata and Storage Backends | sus_meta |
| Attributable Fraction and Number from a DLNM Fit | sus_mod_af |
| Ranked Disease Burden Table Across Cities or Strata | sus_mod_burden |
| Time-Stratified Case-Crossover Analysis for Climate-Health Data | sus_mod_casecrossover |
| Distributed Lag Non-linear Model (DLNM) for Climate-Health Analyses | sus_mod_dlnm |
| Excess Mortality and Morbidity from Climate-Health Time Series | sus_mod_excess |
| Interrupted Time Series Analysis for Health Outcome Counts | sus_mod_its |
| Meta-Regression of Pooled DLNM Estimates with City-Level Covariates | sus_mod_metaregression |
| XGBoost Machine Learning for Climate-Health Outcome Prediction | sus_mod_ml |
| Plots and Tables from an Attributable Fraction Analysis | sus_mod_plot_af |
| Plots and Tables from a City-Level Disease Burden Analysis | sus_mod_plot_burden |
| Scientific Plots and Tables from a DLNM Fit | sus_mod_plot_dlnm |
| Plots and Tables from an XGBoost Machine Learning Model | sus_mod_plot_ml |
| Plots and Tables from a Pooled DLNM Meta-Analysis | sus_mod_plot_pool |
| Plots and Tables from a Multi-Stratum Sensitivity Analysis | sus_mod_plot_sensitivity |
| Visualizations for Space-Time Bayesian Disease Mapping Results | sus_mod_plot_spacetime |
| Visualizations for Bayesian Spatial Disease Mapping Results | sus_mod_plot_spatial_bayes |
| Two-Panel LISA Visualisation: Cluster Map and Moran Scatter Plot | sus_mod_plot_spatial_moran |
| Choropleth Map of Kulldorff Spatial Scan Cluster Results | sus_mod_plot_spatial_scan |
| Plots and Tables from a Climate-Health SWOT Analysis | sus_mod_plot_swot |
| Plots and Tables from an IPCC Vulnerability Index Analysis | sus_mod_plot_vulnerability |
| Two-Stage Multi-City Pooling of DLNM Estimates | sus_mod_pool |
| Stratified Climate-Health Sensitivity Analysis from DLNM Fits | sus_mod_sensitivity |
| Bayesian Spatiotemporal Hierarchical Model with INLA | sus_mod_spacetime_bayes |
| Posterior Exceedance Probabilities from a Spatiotemporal Bayesian Model | sus_mod_spacetime_exceedance |
| Generate Predictions from a Fitted Space-Time Bayesian Model | sus_mod_spacetime_predict |
| Bayesian CAR / BYM Disease Mapping with Climate Covariates | sus_mod_spatial_bayes |
| Global Moran's I and LISA Local Autocorrelation for Health Outcomes | sus_mod_spatial_moran |
| Spatial Regression (SAR / SEM / SDM / SAC) for Climate-Health Associations | sus_mod_spatial_reg |
| Kulldorff Circular Scan Statistic for Spatial Cluster Detection | sus_mod_spatial_scan |
| Build Spatial Weights from Municipality Polygons | sus_mod_spatial_weights |
| SWOT Analysis for Climate-Health Surveillance | sus_mod_swot |
| IPCC 3-Pillar Composite Vulnerability Index for Climate-Health Analysis | sus_mod_vulnerability_index |
| Export a climasus4r Pipeline as a Reproducible Analytical Pipeline (RAP) | sus_rap_export |
| Import and Optionally Run a RAP Recipe | sus_rap_from_recipe |
| Launch an Interactive GUI for Editing and Running RAPs | sus_rap_gui |
| Inspect or Diff rap_object(s) | sus_rap_inspect |
| Execute a targets Pipeline from a RAP | sus_rap_make |
| Read an Exported RAP File | sus_rap_read |
| Export a RAP as a Compact YAML Recipe | sus_rap_recipe |
| Re-execute an Exported RAP | sus_rap_run |
| Generate a targets Pipeline from a climasus4r RAP | sus_rap_targets |
| Scaffold a Reproducible Analytical Pipeline Project | sus_rap_template |
| Update Parameters in an Exported RAP File | sus_rap_update |
| Compute Socioeconomic and Epidemiological Indicators | sus_socio_compute_indicators |
| List Available Indicators in the Catalogue | sus_socio_list_indicators |
| Spatially Link SUS Data to Brazilian Geographic Units | sus_spatial_join |
| Display the climasus4r Pipeline Overview | sus_welcome |
| Reduce climasus_af to a tidy one-row tibble | tidy.climasus_af |
| Tidy a climasus_burden object into a flat tibble | tidy.climasus_burden |
| Tidy a climasus_casecrossover object | tidy.climasus_casecrossover |
| Reduce climasus_dlnm to a tidy one-row tibble | tidy.climasus_dlnm |
| Tidy a climasus_excess object into a one-row summary tibble | tidy.climasus_excess |
| Tidy a climasus_its object | tidy.climasus_its |
| Tidy a climasus_metaregression object into a summary tibble | tidy.climasus_metaregression |
| Tidy a climasus_ml object into a flat predictions tibble | tidy.climasus_ml |
| Tidy a climasus_pool object into a one-row summary tibble | tidy.climasus_pool |
| Tidy a climasus_sensitivity object | tidy.climasus_sensitivity |
| Tidy a climasus_swot object into a flat scores tibble | tidy.climasus_swot |
| Tidy a climasus_vi object into a flat tibble | tidy.climasus_vi |
| Extract variance-covariance from a climasus_metaregression object | vcov.climasus_metaregression |
| Extract pooled variance-covariance from a climasus_pool object | vcov.climasus_pool |
| Write a climasus_df to a persistent DuckDB file | write_duckdb_climasus |
| Write a climasus_df directly to a Parquet file | write_parquet_climasus |
