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spEDM: Spatial Empirical Dynamic Modeling
Inferring causal associations in cross-sectional earth system data through empirical dynamic modeling (EDM), with extensions to convergent cross mapping from Sugihara et al. (2012) <doi:10.1126/science.1227079>, partial cross mapping as outlined in Leng et al. (2020) <doi:10.1038/s41467-020-16238-0>, and cross mapping cardinality as described in Tao et al. (2023)<doi:10.1016/j.fmre.2023.01.007>.
| Version: |
1.4 |
| 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, spData |
| Published: |
2025-02-10 |
| 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 |
| Materials: |
README NEWS |
| CRAN checks: |
spEDM results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=spEDM
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.