1. Introduction to the tEDM package | 2. Example data in the tEDM package | Hong Kong Air Pollution and Cardiovascular Admissions | US County-Level Carbon Emissions Dataset | COVID-19 Infection Counts in Japan | 3. Case studies of the tEDM package | Air Pollution and Cardiovascular Health in Hong Kong | US County Carbon Emissions and Temperature Dynamics | COVID-19 Spread Across Japanese Prefectures | Reference
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:
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✨
DESCRIPTION |NEWS
card.svg |card.png
tEDM/json (API)
| # 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:
causal-analysiscausal-discoverycausal-inferencechaoscppdynamical-systemsempirical-dynamic-modelingtemporal-causal-discoverytemporal-causalitytime-seriestime-series-analysisurban-analyticsurban-data-scienceopenblascppopenmp
Last updated from:ea97238199. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 417 | ||
| linux-devel-x86_64 | OK | 459 | ||
| source / vignettes | OK | 568 | ||
| linux-release-arm64 | OK | 351 | ||
| linux-release-x86_64 | OK | 368 | ||
| macos-release-arm64 | OK | 174 | ||
| macos-release-x86_64 | OK | 488 | ||
| macos-oldrel-arm64 | OK | 124 | ||
| macos-oldrel-x86_64 | OK | 450 | ||
| windows-devel | OK | 204 | ||
| windows-release | OK | 203 | ||
| windows-oldrel | OK | 181 | ||
| wasm-release | OK | 446 |
Exports:ccmcmcembeddedfnniclogistic_mapmultispatialccmpcmsimplexsmap
Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppThreadrlangS7scalestibbletidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| convergent cross mapping | ccm ccm,data.frame-method |
| cross mapping cardinality | cmc cmc,data.frame-method |
| embedding time series data | embedded embedded,data.frame-method |
| false nearest neighbours | fnn fnn,data.frame-method |
| optimal parameter search for intersectional cardinality | ic ic,data.frame-method |
| logistic map | logistic_map |
| multispatial convergent cross mapping | multispatialccm multispatialccm,list-method |
| partial cross mapping | pcm pcm,data.frame-method |
| optimal parameter search for simplex projection | simplex simplex,data.frame-method simplex,list-method |
| optimal parameter search for s-mapping | smap smap,data.frame-method |
