Degrees of Freedom and Confidence Intervals for Partial Least Squares Regression

Documentation for package ‘plsdof’ version 0.2-0

plsdof-package	Degrees of Freedom and Confidence Intervals for Partial Least Squares Regression
aic	Akaike Information Criterion
benchmark.pls	Comparison of model selection criteria for Partial Least Squares Regression.
bic	Bayesian information criterion
coef.plsdof	Regression coefficients
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.
gmdl	Generalized minimum description length
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
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	Degrees of Freedom and Confidence Intervals for Partial Least Squares Regression
tr	Trace of a matrix
vcov.plsdof	Variance-covariance matrix
vvtz	Projectin operator