plsdof: Degrees of Freedom and Statistical Inference for Partial Least Squares Regression

The plsdof package provides Degrees of Freedom estimates for Partial Least Squares (PLS) Regression. Model selection for PLS is based on various information criteria (aic, bic, gmdl) or on cross-validation. Estimates for the mean and covariance of the PLS regression coefficients are available. They allow the construction of approximate confidence intervals and the application of test procedures (Kramer and Sugiyama 2012 <doi:10.1198/jasa.2011.tm10107>). Further, cross-validation procedures for Ridge Regression and Principal Components Regression are available.

Version: 0.3-2
Depends: MASS
Published: 2022-11-30
Author: Nicole Kraemer, Mikio L. Braun
Maintainer: Frederic Bertrand <frederic.bertrand at utt.fr>
BugReports: https://github.com/fbertran/plsdof/issues/
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/fbertran/plsdof/, https://fbertran.github.io/plsdof/
NeedsCompilation: no
Citation: plsdof citation info
Materials: README NEWS ChangeLog
CRAN checks: plsdof results

Documentation:

Reference manual: plsdof.pdf

Downloads:

Package source: plsdof_0.3-2.tar.gz
Windows binaries: r-devel: plsdof_0.3-2.zip, r-release: plsdof_0.3-2.zip, r-oldrel: plsdof_0.3-2.zip
macOS binaries: r-release (arm64): plsdof_0.3-2.tgz, r-oldrel (arm64): plsdof_0.3-2.tgz, r-release (x86_64): plsdof_0.3-2.tgz
Old sources: plsdof archive

Reverse dependencies:

Reverse suggests: bootPLS, plsRbeta, plsRcox, plsRglm

Linking:

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