print.ddsPLS

Function to sum up bootstrap performance results of the ddsPLS algorithm

A sparse Partial Least Squares implementation which uses soft-threshold
estimation of the covariance matrices and therein introduces
sparsity. Number of components and regularization coefficients are automatically set.

Hadrien Lorenzo

ddsPLS

Data-Driven Sparse Partial Least Squares

print.ddsPLS function

<dl><dt>x</dt>
<dd>A ddsPLS object.</dd>
<dt>...</dt>
<dd>Other parameters to be taken into account.</dd></dl>

Arguments

Function to sum up bootstrap performance results of the ddsPLS algorithm — print.ddsPLS

<dl>

<dt>x</dt>
<dd>A ddsPLS object.</dd>


<dt>...</dt>
<dd>Other parameters to be taken into account.</dd>

</dl>

print.ddsPLS: Function to sum up bootstrap performance results of the ddsPLS algorithm

Description

Usage

Arguments

See Also