Package: tEDM 2.0

Wenbo Lyu

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>.

Authors:Wenbo Lyu [aut, cre, cph]

tEDM_2.0.tar.gz
tEDM_2.0.zip(r-4.7)tEDM_2.0.zip(r-4.6)tEDM_2.0.zip(r-4.5)
tEDM_2.0.tgz(r-4.6-x86_64)tEDM_2.0.tgz(r-4.6-arm64)tEDM_2.0.tgz(r-4.5-x86_64)tEDM_2.0.tgz(r-4.5-arm64)
tEDM_2.0.tar.gz(r-4.7-arm64)tEDM_2.0.tar.gz(r-4.7-x86_64)tEDM_2.0.tar.gz(r-4.6-arm64)tEDM_2.0.tar.gz(r-4.6-x86_64)
tEDM_2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
tEDM/json (API)
NEWS

# Install 'tEDM' in R:
install.packages('tEDM', repos = c('https://stscl.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/stscl/tedm/issues

Pkgdown/docs site:https://stscl.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

causal-analysiscausal-discoverycausal-inferencechaoscppdynamical-systemsempirical-dynamic-modelingtemporal-causal-discoverytemporal-causalitytime-seriestime-series-analysisurban-analyticsurban-data-scienceopenblascppopenmp

6.83 score 64 stars 2 scripts 263 downloads 10 exports 28 dependencies

Last updated from:ea97238199. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK205
linux-devel-x86_64OK233
source / vignettesOK293
linux-release-arm64OK198
linux-release-x86_64OK189
macos-release-arm64OK124
macos-release-x86_64OK566
macos-oldrel-arm64OK140
macos-oldrel-x86_64OK364
windows-develOK231
windows-releaseOK213
windows-oldrelOK164
wasm-releaseOK170

Exports:ccmcmcembeddedfnniclogistic_mapmultispatialccmpcmsimplexsmap

Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppThreadrlangS7scalestibbletidyselectutf8vctrsviridisLitewithr

Temporal Empirical Dynamic Modeling

Rendered fromtEDM.Rmdusingknitr::rmarkdownon May 12 2026.

Last update: 2026-03-30
Started: 2025-06-26

Readme and manuals

Help Manual

Help pageTopics
convergent cross mappingccm ccm,data.frame-method
cross mapping cardinalitycmc cmc,data.frame-method
embedding time series dataembedded embedded,data.frame-method
false nearest neighboursfnn fnn,data.frame-method
optimal parameter search for intersectional cardinalityic ic,data.frame-method
logistic maplogistic_map
multispatial convergent cross mappingmultispatialccm multispatialccm,list-method
partial cross mappingpcm pcm,data.frame-method
optimal parameter search for simplex projectionsimplex simplex,data.frame-method simplex,list-method
optimal parameter search for s-mappingsmap smap,data.frame-method