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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 |
DOI: | 10.32614/CRAN.package.GIMMEgVAR |
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 |
Reference manual: | GIMMEgVAR.pdf |
Vignettes: |
GIMMEgVAR Vignette |
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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.