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: 0.2-6
Depends: MASS
Published: 2013-03-19
Author: Nicole Kraemer, Mikio L. Braun
Maintainer: Nicole Kraemer <kraemer at ma.tum.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: plsdof citation info
Materials: ChangeLog
CRAN checks: plsdof results

Downloads:

Reference manual: plsdof.pdf
Package source: plsdof_0.2-6.tar.gz
MacOS X binary: plsdof_0.2-6.tgz
Windows binary: plsdof_0.2-6.zip
Old sources: plsdof archive

Reverse dependencies:

Reverse imports: plsRbeta
Reverse suggests: plsRcox, plsRglm