modelSelection: High-Dimensional Model Selection
Model selection and averaging for regression, generalized linear models, generalized additive models, graphical models and mixtures, focusing on Bayesian model selection and information criteria (Bayesian information criterion etc.). See Rossell (2025) <doi:10.5281/zenodo.17119597> (see the URL field below for its URL) for a hands-on book describing the methods, examples and suggested citations if you use the package.
Version:
1.0.4
Depends:
R (≥ 2.14.0), methods
Imports:
Rcpp (≥ 0.12.16),
dplyr,
glmnet,
huge,
intervals,
L0Learn,
Matrix,
mclust,
mgcv,
mvtnorm,
ncvreg,
pracma,
sparseMatrixStats,
survival
Published:
2025年10月21日
Author:
David Rossell [aut, cre],
John D. Cook [ctb],
Donatello Telesca [aut],
P. Roebuck [ctb],
Oriol Abril [aut],
Miquel Torrens [aut],
Peter Mueller [ctb],
William Hallahan [ctb]
Maintainer:
David Rossell <rosselldavid at gmail.com>
NeedsCompilation:
yes
Documentation:
Downloads:
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