pls1c

 A numeric matrix assumed to have been centred so columns sum
  to zero.

 A numeric vector assumed to sum to zero.

The number of PLS factors in the model, which must be
  less than or equal to the rank of <code>X</code>.

dimension


  This function fits a partial least squares model based on the modified
  Helland algorithm. This is an internal function and is not intended to
  be called by the end user.


 internal

This package can be used to classify microarray data using one of three
penalized regression methods; partial least squares, principal components
regression, or ridge regression.

James W MacDonald

pdmclass

Classification of Microarray Samples using Penalized Discriminant Methods

pls1c function

A numeric matrix assumed to have been centred so columns sum
  to zero.

The number of PLS factors in the model, which must be
  less than or equal to the rank of <code>X</code>.

This function fits a partial least squares model based on the modified
  Helland algorithm. This is an internal function and is not intended to
  be called by the end user.

pls1c: Function to Fit Modified Helland Algorithm

Description

Usage

Arguments

Value

References