Inferring causation from time series data through empirical dynamic modeling (EDM), with methods such as 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: 1.0 Depends: R (≥ 4.1.0) Imports: dplyr, ggplot2, methods, Rcpp LinkingTo: Rcpp, RcppThread, RcppArmadillo Suggests: RcppThread, RcppArmadillo, readr, plot3D, spEDM, knitr, rmarkdown, purrr, tidyr, cowplot Published: 2025-07-15 DOI: 10.32614/CRAN.package.tEDM Author: Wenbo Lv [aut, cre, cph] Maintainer: Wenbo Lv <lyu.geosocial at gmail.com> BugReports: https://github.com/stscl/tEDM/issues License: GPL-3 URL: https://stscl.github.io/tEDM/, https://github.com/stscl/tEDM NeedsCompilation: yes Materials: README, NEWS CRAN checks: tEDM results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=tEDM to link to this page.
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