Data and setup | Coarse-to-fine dynamic spatial GLMM (CF-DGLM) | Space-time prediction | Predictive values at observed time points | Forecasting an unobserved time point | Prediction at new sites and times with predict() | Predictive quantiles and the size of the fitted object | Multiscale space-time pattern extraction | Interactive mapping | Reference

Example 1: Count data modeling for disease mapping | Data and setup | Coarse-to-fine spatial GLMM (CF-GLM) | Disease mapping | Predictive values | Multiscale spatial pattern/feature extraction | Example 2: Binary data modeling and prediction | Mapping | Prediction at new sites with predict() | Interactive mapping | Reference

Data and setup | Coarse-to-fine spatial modeling | Mapping | Predictive values | Prediction at new sites with predict() | Multiscale spatial pattern/feature extraction | Interactive mapping | Reference

Data and setup | Coarse-to-fine spatial downscaling (CF-DS) | Mapping | Downscaling result | Predictive standard deviations | Reference

Introduction | Regression with residual spatio-temporal dependence | Regression with spatio-temporally varying coefficients (STVCs) | Implemented extentions | Reference

Introduction | Gaussian spatial additive mixed models | Non-Gaussian spatial regression models | Spatially filtered unconditional quantile regression | Low rank spatial econometric models | Tips for modeling large samples | Reference