Showing 4 of total 4 results (show query)
gateslab
gimme:Group Iterative Multiple Model Estimation
Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.
Maintained by Kathleen M Gates. Last updated 9 days ago.
26 stars 7.61 score 53 scripts
svazzole
sparsevar:Sparse VAR/VECM Models Estimation
A wrapper for sparse VAR/VECM time series models estimation using penalties like ENET (Elastic Net), SCAD (Smoothly Clipped Absolute Deviation) and MCP (Minimax Concave Penalty). Based on the work of Sumanta Basu and George Michailidis <doi:10.1214/15-AOS1315>.
Maintained by Simone Vazzoler. Last updated 4 years ago.
econometricslassomcpscadsparsestatisticstime-seriesvarvecm
11 stars 5.69 score 30 scripts 1 dependents
andreamrau
ebdbNet:Empirical Bayes Estimation of Dynamic Bayesian Networks
Infer the adjacency matrix of a network from time course data using an empirical Bayes estimation procedure based on Dynamic Bayesian Networks.
Maintained by Andrea Rau. Last updated 2 years ago.
4 stars 4.28 score 19 scripts
cran
mlVAR:Multi-Level Vector Autoregression
Estimates the multi-level vector autoregression model on time-series data. Three network structures are obtained: temporal networks, contemporaneous networks and between-subjects networks.
Maintained by Sacha Epskamp. Last updated 1 years ago.
2.56 score 2 dependents