Citation for package GD | Authors’ affiliations | 1. Introduction to GD package | 1.1 The model can be used to address following issues: | 1.2 The GD package makes following steps fast and easy: | 1.3 Start from the one-step function: gdm (Highly Recommended) | 1.4 Advanced models | 2. Geographical detector model | 3. Spatial data discretization | 3.1 Discretization with given parameters: disc | 3.2 Optimal discretization: optidisc | 4. Geographical detectors | 4.1 Factor detector: gd | 4.2 Risk detector: riskmean and gdrisk | 4.3 Interaction detector: gdinteract | 4.4 Ecological detector: gdeco | 5. Comparison of size effects of spatial unit | Reference

Citation for package geosimilarity | 1. Introduction to geosimilarity package | 2. Spatial prediction using GOS model | 2.1 Characterizing geographical configurations | 2.2 Determining the optimal similarity | 2.3 Spatial prediction | 2.4 Model evaluation

Introduction to the localsp package | 1.1 This package can be used to address following issues: | 1.2 How to install this package: | 1.4 Example data in this package: | Case study: identifying local stratified determinants of Mountain glacier thickness | 2.1 Local extent exploration | 2.2 Local power of determinants of individual variables | Reference

Improving Model Fitting Utilizing Geographical Complexity in Spatial Regression Tasks | Incorporating the geographical complexity of each independent variable into the model's explanatory variables | GCMLR 0.6215 0.6024 | Using spatial weight matrices that account for geographical complexity in spatial regression | GCSEM -1364 -1322 693.1 | geographical complexity-geographically weighted regression | GeoCGWR 0.836 0.8319 -1445 0.01923

Calculation methods of geographical complexity | Considering the geographical complexity with spatial local dependencies | Considering the geographical complexity with geographical configurations similarities | Firstly, calculate global similarity: | The geographic complexity is then calculated: | Cases for computing geographical complexity | Geographical Complexity of Individual Variables | Geographical Complexity of Multiple Variables

Introduction to SecDim package | Cross validation