Analysis of Spatial Stratified Heterogeneity
gdverse consolidates cutting-edge SSH methodologies into a unified toolkit, redefining spatial association measurement as the evolutionary successor to geodetector and GD in the R ecosystem.
Current models and functions provided by gdverse are:
| Model | Function | Support |
|---|---|---|
| GD | gd() | ✔️ |
| OPGD | opgd() | ✔️ |
| GOZH | gozh() | ✔️ |
| LESH | lesh() | ✔️ |
| SPADE | spade() | ✔️ |
| IDSA | idsa() | ✔️ |
| RGD | rgd() | ✔️ |
| RID | rid() | ✔️ |
| SRSGD | srsgd() | ✔️ |
- Install from CRAN with:
install.packages("gdverse", dep = TRUE)- Install development binary version from R-universe with:
install.packages('gdverse', repos = c("https://stscl.r-universe.dev", "https://cloud.r-project.org"), dep = TRUE)- Install development source version from GitHub with:
# install.packages("devtools") devtools::install_github("stscl/gdverse", build_vignettes = TRUE, dep = TRUE)✨ Please ensure that Rcpp is properly installed and the appropriate C++ compilation environment is configured in advance if you want to install gdverse from github.
✨ The gdverse package supports the use of robust discretization for the robust geographical detector and robust interaction detector. For details on using them, please refer to https://stscl.github.io/gdverse/articles/rgdrid.html.
library(gdverse) data("ndvi") ndvi ## # A tibble: 713 × 7 ## NDVIchange Climatezone Mining Tempchange Precipitation GDP Popdensity ## <dbl> <chr> <fct> <dbl> <dbl> <dbl> <dbl> ## 1 0.116 Bwk low 0.256 237. 12.6 1.45 ## 2 0.0178 Bwk low 0.273 214. 2.69 0.801 ## 3 0.138 Bsk low 0.302 449. 20.1 11.5 ## 4 0.00439 Bwk low 0.383 213. 0 0.0462 ## 5 0.00316 Bwk low 0.357 205. 0 0.0748 ## 6 0.00838 Bwk low 0.338 201. 0 0.549 ## 7 0.0335 Bwk low 0.296 210. 11.9 1.63 ## 8 0.0387 Bwk low 0.230 236. 30.2 4.99 ## 9 0.0882 Bsk low 0.214 342. 241 20.0 ## 10 0.0690 Bsk low 0.245 379. 42.0 7.50 ## # ℹ 703 more rowsdiscvar = names(ndvi)[-1:-3] discvar ## [1] "Tempchange" "Precipitation" "GDP" "Popdensity" ndvi_opgd = opgd(NDVIchange ~ ., data = ndvi, discvar = discvar, cores = 6) ndvi_opgd ## *** Optimal Parameters-based Geographical Detector ## Factor Detector ## ## | variable | Q-statistic | P-value | ## |:-------------:|:-----------:|:--------:| ## | Precipitation | 0.8693505 | 2.58e-10 | ## | Climatezone | 0.8218335 | 7.34e-10 | ## | Tempchange | 0.3330256 | 1.89e-10 | ## | Popdensity | 0.1990773 | 6.60e-11 | ## | Mining | 0.1411154 | 6.73e-10 | ## | GDP | 0.1004568 | 3.07e-10 |g = gozh(NDVIchange ~ ., data = ndvi) g ## *** Geographically Optimal Zones-based Heterogeneity Model ## Factor Detector ## ## | variable | Q-statistic | P-value | ## |:-------------:|:-----------:|:--------:| ## | Precipitation | 0.87255056 | 4.52e-10 | ## | Climatezone | 0.82129550 | 2.50e-10 | ## | Tempchange | 0.33324945 | 1.12e-10 | ## | Popdensity | 0.22321863 | 3.00e-10 | ## | Mining | 0.13982859 | 6.00e-11 | ## | GDP | 0.09170153 | 3.96e-10 |Please cite gdverse as:
Lv, W., Lei, Y., Liu, F., Yan, J., Song, Y. and Zhao, W. (2025), gdverse: An R Package for Spatial Stratified Heterogeneity Family. Transactions in GIS, 29(2). https://doi.org/10.1111/tgis.70032 A BibTeX entry for LaTeX users is:
@article{lyu2025gdverse, title={{gdverse}: An {R} Package for Spatial Stratified Heterogeneity Family}, volume={29}, ISSN={1467-9671}, DOI={10.1111/tgis.70032}, number={2}, journal={Transactions in GIS}, publisher={Wiley}, author={Lv, Wenbo and Lei, Yangyang and Liu, Fangmei and Yan, Jianwu and Song, Yongze and Zhao, Wufan}, year={2025}, month={mar} }