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tEDM

Temporal Empirical Dynamic Modeling

Overview

The tEDM package provides a suite of tools for exploring and quantifying causality in time series using Empirical Dynamic Modeling (EDM). It is particularly designed to detect, differentiate, and reconstruct causal dynamics in systems where traditional assumptions of linearity and stationarity may not hold.

The package implements four fundamental EDM-based methods:

Installation

  • Install from CRAN with:
install.packages("tEDM", dep = TRUE)
install.packages("tEDM",
                 repos = c("https://stscl.r-universe.dev",
                           "https://cloud.r-project.org"),
                 dep = TRUE)
  • Install from source code on GitHub with:
if (!requireNamespace("devtools")) {
    install.packages("devtools")
}
devtools::install_github("stscl/tEDM",
                         #build_vignettes = TRUE,
                         dep = TRUE)

Reference

Sugihara, G., May, R., Ye, H., Hsieh, C., Deyle, E., Fogarty, M., Munch, S., 2012. Detecting Causality in Complex Ecosystems. Science 338, 496–500. https://doi.org/10.1126/science.1227079.

Leng, S., Ma, H., Kurths, J., Lai, Y.-C., Lin, W., Aihara, K., Chen, L., 2020. Partial cross mapping eliminates indirect causal influences. Nature Communications 11. https://doi.org/10.1038/s41467-020-16238-0.

Tao, P., Wang, Q., Shi, J., Hao, X., Liu, X., Min, B., Zhang, Y., Li, C., Cui, H., Chen, L., 2023. Detecting dynamical causality by intersection cardinal concavity. Fundamental Research. https://doi.org/10.1016/j.fmre.2023.01.007.

Clark, A.T., Ye, H., Isbell, F., Deyle, E.R., Cowles, J., Tilman, G.D., Sugihara, G., 2015. Spatial convergent cross mapping to detect causal relationships from short time series. Ecology 96, 1174–1181. https://doi.org/10.1890/14-1479.1.

 

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Version

Install

install.packages('tEDM')

Version

1.0

License

GPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

Wenbo Lv

Last Published

July 15th, 2025

Functions in tEDM (1.0)

ic

intersection cardinality
ccm

convergent cross mapping
embedded

embedding time series data
cmc

cross mapping cardinality
logistic_map

logistic map
fnn

false nearest neighbours
pcm

partial cross mapping
multispatialccm

multispatial convergent cross mapping
simplex

simplex forecast
smap

smap forecast