koplsDemo {kopls}R Documentation

K-OPLS demonstration procedure

Description

This script contains a demonstration of the functionality in the kopls package using a simulated data set.

Usage

demo(koplsDemo)

Details

The data set is represented by 1000 spectral variables from two different classes and is available in the an attached data set. The demonstration essentially consists of two main steps.

The first step is to demonstrate how K-OPLS handles the model evaluation (using cross-validation), model building and subsequent classification of external data from a non-linear data set. The second step is to demonstrate how K-OPLS works in the presence of response-independent (Y-orthogonal) variation, using the same data set but with a strong systematic class-specific disturbance added.

The koplsExample data set contains the following objects:
Xtr The training data matrix, with 400 observations
and 1000 spectral variables.
Xte The test data matrix, with 400 observations
and 1000 spectral variables.
Xtro Same data as 'Xtr', but with class-specific
systematic noise added.
Xteo Same data as 'Xte', but with class-specific
systematic noise added.
Ytr A binary matrix of class assignments for the
training data.
Yte A binary matrix of class assignments for the
test data.
pch.vec A vector with character indices
(for plotting).
col.vec A vector with colors (for plotting).

Author(s)

Max Bylesjo and Mattias Rantalainen

References

Rantalainen M, Bylesjo M, Cloarec O, Nicholson JK, Holmes E and Trygg J. Kernel-based orthogonal projections to latent structures (K-OPLS), J Chemometrics 2007; 21:376-385. doi:10.1002/cem.1071.


[Package kopls version 1.0.3 Index]