Overview | Data requirements | Formatting dates | Descriptor list | Computing descriptors

Overview | 0. Load the package and sample data | 1. Key c4h_downscale arguments | 2. Downscaling methods (gridded data) | Method 1: Interpolation | Method 2: Interpolation plus bias correction | Method 3: Interpolation plus linear regression | Method 4: Analogs | 3. Downscaling to point locations | 4. Calibration | 5. Considerations for downscaling common variables | Interpolation-based methods | Specific recommendations for precipitation downscaling | General recommendations | Parameter selection

Overview | 0. Load the package | 1. c4h_get arguments | 2. c4h_get_help | 3. Specifying arguments in c4h_get() | Specifying temporal range | Specifying spatial extent | Specifying variables | Specifying the file path and name | 4. Obtain your Personal Access Token (PAT) | 5. Example downloads | 5.1. ERA5-Land data | 5.2. Hindcast data | 5.3. Forecast data

Overview | Glossary

Overview | Installation | Data requirements | clim4health structure | 1. Obtain input data | 2. Transform and process the data | 3. Prepare outputs | clim4health workflow | 1. Loading, inspecting, and preprocessing data | Dataset description | Data preprocessing | Plot the raw data | 2. Processing the data | Spatial aggregation | Downscaling | Verification and postprocessing | Masking data | Aggregating data temporally | Collapsing data across a dimension | 3. Outputting the data | Convert data from an s2dv_cube to a different data type | Save the data

Overview | 0. Load the package and sample data | 1. Key c4h_verify arguments | 2. Verification metrics | "BSS" - Brier Skill Score | "RPSS" - Ranked Probability Skill Score | "CRPSS" - Continuous Ranked Probability Skill Score | "AbsBiasSS" - Absolute Bias Skill Score | "MSE" - Mean Squared Error | "MSSS" - Mean Squared Error Skill Score | "RMSE" - Root Mean Squared Error | "RMSSS" - Root Mean Square Skill Score | "ROCSS" - Relative Operating Characteristic Skill Score | Statistical Significance | 3. Example skill assessment | Choosing arguments in c4h_verify | ref | brier_thresholds | prob_thresholds | sig_method and sig_method.type | alpha | ncores | N.eff | indices_for_clim | cross.val and clim.cross.val | weights_exp and weights_ref | comp_dim and limits | conf | na.rm | sign and pval | rocss_cat

Overview | 0. Load the package | 1. Forecasts, hindcasts, and reanalyses | 2. Climate data in clim4health | Loading multi-dimensional data with c4h_load | Loading example data | The forecast data is stored with dimensions | The hindcast data is stored with dimensions | The reanalysis data is stored with dimensions | Exploring the loaded data | Data dimensions in clim4health | Exploring the s2dv_cube structure | 3. Constructing an s2dv_cube from scratch | 1. Load the data | 2. Reshape the data | 3. Add dimensions, coordinates, and attributes | 4. Create the s2dv_cube object

Overview | GHRmodel formula helper functions | 0. Prepare data | Load libraries | Data pre-processing | Spatial data and graphs | Pre-process covariates | Lagged covariates | Define priors | Example 1: GHRmodel helper functions | 1. Model development | Select variables | Linear covariates | Non-linear covariates | Non-linear covariates replicated by group | Covariates for multivariate models | Add a covariate to all covariate lists | Interacting covariates | Varying covariates | Varying vs. Replicated Effects in INLA | Write INLA-compatible model formulas | 2. Model fitting | 3. Model evaluation | Interaction effects | Varying linear coefficients | Replicated nonlinear coefficients | Example 2: INLA-compatible formulas | References

Overview | Example: DLNMs in GHRmodel | 0. Prepare data | Load libraries | Data pre-processing | Spatial data and graphs | 1. Model development | One-dimensional basis matrix | Cross-basis matrix | Model formulas including DLNM terms | 2. Fit DLNMs with INLA | 3. DLNM output | One-basis terms | Cross-basis terms | References

Overview | Installation | Data requirements | Methodology | GHRmodel structure | 1. Model development | 2. Model fitting | 3. Model evaluation | GHRmodel workflow | 0. Data | Dataset description | Data pre-processing | Spatial data and graphs | Create lagged covariates | Write covariates | Write formulas | Rank models | Posterior predictive checks | Goodness-of-fit metrics | Fitted vs. Observed | Covariate effects | Evaluate random effects | 4. Iterative model selection | Subset models | Extract covariates | Add an additional covariate | Fit new models | Combine models | Evaluate combined models | References

Overview | Data requirements | Covariates, case counts, and incidence rates | Spatial and temporal aggregations | Color palettes | Plot types | Time series | Dual-axis time series | Heatmap | Seasonality | Map | Bivariate | Correlation | Compare