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. Further, cross-validation procedures for Ridge Regression and Principal Components Regression are available.

Version: 0.2-9
Depends: MASS
Published: 2019-01-31
Author: Nicole Kraemer, Mikio L. Braun
Maintainer: Frederic Bertrand <frederic.bertrand at math.unistra.fr>
BugReports: https://github.com/fbertran/plsdof/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/fbertran/plsdof
NeedsCompilation: no
Citation: plsdof citation info
Materials: NEWS ChangeLog
CRAN checks: plsdof results

Downloads:

Reference manual: plsdof.pdf
Package source: plsdof_0.2-9.tar.gz
Windows binaries: r-devel: plsdof_0.2-9.zip, r-release: plsdof_0.2-9.zip, r-oldrel: plsdof_0.2-9.zip
macOS binaries: r-release: plsdof_0.2-9.tgz, r-oldrel: plsdof_0.2-9.tgz
Old sources: plsdof archive

Reverse dependencies:

Reverse suggests: plsRbeta, plsRcox, plsRglm

Linking:

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