GIMMEgVAR: Group Iterative Multiple Model Estimation with 'graphicalVAR'

Data-driven approach for arriving at person-specific time series models from within a Graphical Vector Autoregression (VAR) framework. 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. All estimates are obtained uniquely for each individual in the final models. The method for the 'graphicalVAR' approach is found in Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.

Version:	0.1.0
Depends:	R (≥ 3.5.0)
Imports:	graphicalVAR, here, qgraph, png
Suggests:	knitr, rmarkdown
Published:	2024-05-16
Author:	Sandra Williams Lee [aut, cre], Kathleen M. Gates [aut]
Maintainer:	Sandra Williams Lee <wsandra at live.unc.edu>
License:	GPL-2
NeedsCompilation:	no
Materials:	README
CRAN checks:	GIMMEgVAR results

Documentation:

Reference manual:	GIMMEgVAR.pdf
Vignettes:	GIMMEgVAR Vignette

Downloads:

Package source:	GIMMEgVAR_0.1.0.tar.gz
Windows binaries:	r-devel: GIMMEgVAR_0.1.0.zip, r-release: GIMMEgVAR_0.1.0.zip, r-oldrel: GIMMEgVAR_0.1.0.zip
macOS binaries:	r-release (arm64): GIMMEgVAR_0.1.0.tgz, r-oldrel (arm64): GIMMEgVAR_0.1.0.tgz, r-release (x86_64): GIMMEgVAR_0.1.0.tgz, r-oldrel (x86_64): GIMMEgVAR_0.1.0.tgz

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