tEDM: Temporal Empirical Dynamic Modeling

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 introduced by Leng et al. (2020) <doi:10.1038/s41467-020-16238-0>, and cross mapping cardinality described in Tao et al. (2023) <doi:10.1016/j.fmre.2023.01.007>, following a systematic description proposed in Lyu et al. (2026) <doi:10.1016/j.compenvurbsys.2026.102435>.

Version:	1.3
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:	2026-03-30
DOI:	10.32614/CRAN.package.tEDM
Author:	Wenbo Lyu [aut, cre, cph]
Maintainer:	Wenbo Lyu <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
Citation:	tEDM citation info
Materials:	README, NEWS
CRAN checks:	tEDM results

Documentation:

Reference manual:	tEDM.html , tEDM.pdf
Vignettes:	tEDM (source)

Downloads:

Package source:	tEDM_1.3.tar.gz
Windows binaries:	r-devel: tEDM_1.2.zip, r-release: tEDM_1.2.zip, r-oldrel: tEDM_1.2.zip
macOS binaries:	r-release (arm64): tEDM_1.3.tgz, r-oldrel (arm64): tEDM_1.2.tgz, r-release (x86_64): tEDM_1.3.tgz, r-oldrel (x86_64): tEDM_1.3.tgz
Old sources:	tEDM archive

Reverse dependencies:

Reverse suggests:

infocausality, infoxtr, pc

Linking:

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