status

physiopathological status of men in a human cohort study

datasets

Several functions are provided to implement a MBPLSDA : components search, optimal model components number search, optimal model validity test by permutation tests, observed values evaluation of optimal model parameters and predicted categories, bootstrap values evaluation of optimal model parameters and predicted cross-validated categories. The use of this package is described in Brandolini-Bunlon et al (2019. Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data. Metabolomics, 15(10):134).

Marion Brandolini-Bunlon

packMBPLSDA

Multi-Block Partial Least Squares Discriminant Analysis

status function

A data frame with 40 observations on the following variable.<dl class="dl-horizontal">
 <dt><code>status</code></dt><dd>a factor with levels <code>cas</code> <code>temoin</code></dd>
 </dl>

Format

physiopathological status data — status

A data frame with 40 observations on the following variable.<dl class='dl-horizontal'>
 <dt><code>status</code></dt><dd>a factor with levels <code>cas</code> <code>temoin</code></dd>
 </dl>

status: physiopathological status data

Description

Usage

Arguments

Format

Details

Examples