spEDM: Spatial Empirical Dynamic Modeling
Inferring causation from spatial cross-sectional data through empirical dynamic modeling (EDM), with methodological extensions including geographical convergent cross mapping from Gao et al. (2023) <doi:10.1038/s41467-023-41619-6>, as well as the spatial causality test following the approach of Herrera et al. (2016) <doi:10.1111/pirs.12144>, together with geographical pattern causality proposed in Zhang et al. (2025) <doi:10.1080/13658816.2025.2581207>.
| Version: | 1.9 |
| Depends: | R (≥ 4.1.0) |
| Imports: | dplyr,ggplot2, methods,sdsfun (≥ 0.7.0),sf,terra |
| LinkingTo: | Rcpp,RcppThread,RcppArmadillo |
| Suggests: | knitr,Rcpp,RcppThread,RcppArmadillo,rmarkdown,readr,plot3D |
| Published: | 2025-11-30 |
| DOI: | 10.32614/CRAN.package.spEDM |
| Author: | Wenbo Lv [aut, cre, cph] |
| Maintainer: | Wenbo Lv <lyu.geosocial at gmail.com> |
| BugReports: | https://github.com/stscl/spEDM/issues |
| License: | GPL-3 |
| URL: | https://stscl.github.io/spEDM/,https://github.com/stscl/spEDM |
| NeedsCompilation: | yes |
| Citation: | spEDM citation info |
| Materials: | README,NEWS |
| CRAN checks: | spEDM results |
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