doi:10.18637/jss.v102.i04> and associated publications.">

rags2ridges: Ridge Estimation of Precision Matrices from High-Dimensional Data (original) (raw)

Proper L2-penalized maximum likelihood estimators for precision matrices and supporting functions to employ these estimators in a graphical modeling setting. For details, see Peeters, Bilgrau, & van Wieringen (2022) <doi:10.18637/jss.v102.i04> and associated publications.

Version: 2.2.7
Depends: R (≥ 2.15.1)
Imports: igraph, stats, methods, expm, reshape, ggplot2, Hmisc, fdrtool, snowfall, sfsmisc, utils, grDevices, graphics, gRbase, RBGL, graph, Rcpp, RSpectra
LinkingTo: Rcpp, RcppArmadillo
Suggests: KEGGgraph, testthat, knitr, rmarkdown
Published: 2023-10-14
DOI: 10.32614/CRAN.package.rags2ridges
Author: Carel F.W. PeetersORCID iD [aut, cre, cph], Anders Ellern BilgrauORCID iD [aut, cph], Wessel N. van WieringenORCID iD [aut]
Maintainer: Carel F.W. Peeters <carel.peeters at wur.nl>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://cfwp.github.io/rags2ridges/,https://github.com/CFWP/rags2ridges
NeedsCompilation: yes
Citation: rags2ridges citation info
Materials: README NEWS
CRAN checks: rags2ridges results

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