krylov

This function computes the Krylov sequence of a matrix and a vector.

math

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.

Frederic Bertrand

plsdof

Degrees of Freedom and Statistical Inference for Partial Least
Squares Regression

krylov function

<dl><dt>A</dt>
<dd>square matrix of dimension p x p.</dd>
<dt>b</dt>
<dd>vector of length p</dd>
<dt>m</dt>
<dd>length of the Krylov sequence</dd></dl>

Arguments

Author

Krylov sequence — krylov

<dl>

<dt>A</dt>
<dd>square matrix of dimension p x p.</dd>


<dt>b</dt>
<dd>vector of length p</dd>


<dt>m</dt>
<dd>length of the Krylov sequence</dd>

</dl>

krylov: Krylov sequence

Description

Usage

Value

Arguments

Author

Examples