
TemporalEmpiricalDynamicModeling
ThetEDM package provides a suite of tools for exploringand quantifying causality in time series using Empirical DynamicModeling (EDM). It is particularly designed to detect, differentiate,and reconstruct causal dynamics in systems where traditional assumptionsof linearity and stationarity may not hold.
The package implements four fundamental EDM-based methods:
Convergent CrossMapping (CCM) – for detecting nonlinear causalrelationships in time series.
Partial CrossMapping (PCM) – for disentangling direct from indirectcausal influences.
Cross MappingCardinality (CMC) – for identifying time-varying orstate-dependent causal linkages.
MultispatialConvergent Cross Mapping (MultispatialCCM) – forreconstructing causal dynamics from replicated time series acrossmultiple spatial locations.
Refer to the package documentationhttps://stscl.github.io/tEDM/ for more detailedinformation.
install.packages("tEDM",dep =TRUE)install.packages("tEDM",repos =c("https://stscl.r-universe.dev","https://cloud.r-project.org"),dep =TRUE)if (!requireNamespace("devtools")) {install.packages("devtools")}devtools::install_github("stscl/tEDM",#build_vignettes = TRUE,dep =TRUE)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 byintersection 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 detectcausal relationships from short time series. Ecology 96, 1174–1181.https://doi.org/10.1890/14-1479.1.