Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

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.

Functions (24)

benchmark.pls

Comparison of model selection criteria for Partial Least Squares Regression.

benchmark.regression

Comparison of Partial Least Squares Regression, Principal Components Regression and Ridge Regression.

coef.plsdof

Regression coefficients

compute.lower.bound

Lower bound for the Degrees of Freedom

dA

Derivative of normalization function

dnormalize

Derivative of normalization function

dvvtz

First derivative of the projection operator

first.local.minimum

Index of the first local minimum.

information.criteria

Information criteria

kernel.pls.fit

Kernel Partial Least Squares Fit

krylov

Krylov sequence

linear.pls.fit

Linear Partial Least Squares Fit

normalize

Normalization of vectors

pcr

Principal Components Regression

pcr.cv

Model selection for Princinpal Components regression based on cross-validation

pls.cv

Model selection for Partial Least Squares based on cross-validation

pls.dof

Computation of the Degrees of Freedom

pls.ic

Model selection for Partial Least Squares based on information criteria

pls.model

Partial Least Squares

plsdof-package

Degrees of Freedom and Statistical Inference for Partial Least Squares Regression

ridge.cv

Ridge Regression.

tr

Trace of a matrix

vcov.plsdof

Variance-covariance matrix

vvtz

Projectin operator

plsdof

Degrees of Freedom and Statistical Inference for Partial Least Squares Regression

v0.3-0
GPL (>= 2)
Authors
Nicole Kraemer, Mikio L. Braun
Initial release
2021-03-13

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.