PLSR: Partial least squares regression

In structToolbox: Data processing & analysis tools for Metabolomics and other omics

Description

PLS is a multivariate regression technique that extracts latent variables maximising covariance between the input data and the response. For regression the response is a continuous variable.

Usage

PLSR(number_components = 2, factor_name, ...)

Arguments

number_components	(numeric, integer) The number of PLS components. The default is 2.
factor_name	(character) The name of a sample-meta column to use.
...	Additional slots and values passed to struct_class.

Details

This object makes use of functionality from the following packages:

• pls

Value

A PLSR object.

References

Mevik B, Wehrens R, Liland K (2020). pls: Partial Least Squares and Principal Component Regression. R package version 2.7-3, https://CRAN.R-project.org/package=pls.

Examples

M = PLSR(factor_name='run_order')

structToolbox documentation built on Nov. 8, 2020, 6:54 p.m.