swMATH ID: 15374
Software Authors: Abegaz, Fentaw; Wit, Ernst
Description: R package SparseTSCGM: Sparse Time Series Chain Graphical Models. Computes sparse vector autoregressive coefficients and precision matrices for time series chain graphical models. Computes sparse autoregressive coefficient and precision matrices for time series chain graphical models(TSCGM). These models provide an effeicient way of simultaneously dealing with Gaussian graphical models (undirected graphs for instantaneous interactions) and Bayesian networks (directed graphs for dynamic interactions) for reconstructing instantaneous and dynamic networks from repeated multivariate time series data.
Homepage: https://cran.r-project.org/web/packages/SparseTSCGM/index.html
Source Code:  https://github.com/cran/SparseTSCGM
Dependencies: R
Keywords: Time Series Chain Graphical Models; TSCGM
Related Software: tergm; gimme; sparsevar; nets; autovarCore; tnam; networkTomography; NetOrigin; hybridModels; EpiILMCT; EpiILM; latentnet; HLSM; collpcm; igraph; R; GNAR; forecast; fields; mlVAR
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