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Pattern Causality Analysis
pc is an R package for pattern-based causality analysis in both time series and spatial cross-sectional data. It uses symbolic pattern representations and cross mapping to detect directional interactions and infer causal structure from temporal dynamics and spatial snapshots. Built on a high-performance C++ backend with a lightweight R interface, pc provides efficient and flexible tools for data-driven causality analysis.
Refer to the package documentation https://stscl.github.io/pc/ for more detailed information.
- Install from CRAN with:
install.packages("pc", dependencies = TRUE)- Install binary version from R-universe with:
install.packages("pc",
repos = c("https://stscl.r-universe.dev",
"https://cloud.r-project.org"),
dependencies = TRUE)- Install from source code on GitHub with:
if (!requireNamespace("pak")) {
install.packages("pak")
}
pak::pak("stscl/pc", dependencies = TRUE)Stavroglou, S.K., Pantelous, A.A., Stanley, H.E., Zuev, K.M., 2019. Hidden interactions in financial markets. Proceedings of the National Academy of Sciences 116, 10646–10651. https://doi.org/10.1073/pnas.1819449116.
Stavroglou, S.K., Pantelous, A.A., Stanley, H.E., Zuev, K.M., 2020. Unveiling causal interactions in complex systems. Proceedings of the National Academy of Sciences 117, 7599–7605. https://doi.org/10.1073/pnas.1918269117.
Zhang, Z., Wang, J., 2025. A model to identify causality for geographic patterns. International Journal of Geographical Information Science 1–21. https://doi.org/10.1080/13658816.2025.2581207.