SparseTSCGM swMATH ID: 15374 Software Authors: Fentaw Abegaz; Ernst Wit 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: fields; forecast; mlVAR; mgm; graphicalVAR; gimme; vars; sparsevar; nets; autovarCore; tnam; networkTomography; NetOrigin; hybridModels; EpiILMCT; EpiILM; epinet; dynsbm; tergm; blockmodels Cited in: 0 Publications