Full-rank Partial Least squares and Partial Least squares regression

Version 1.0.0.0 (5.41 MB) by Filippo Amato
Multivariate data analysis - modeling
0.0
(0)
546 Downloads
Updated 17 Aug 2015
View License on GitHub

Full- and partial-rank Partial Least Squares Regression.
The functions accept X and Y data either as matrices or tables. X and Y are converted to matrix and processed. The optimal number of PLS components is found by Leave-one-out cross-validation but it can be modified by the user. Outputs are organized in user-defined structure variable and a set of figures is generated. MATLAB workspace with three example data is given.

Cite As

Filippo Amato (2026). Full-rank Partial Least squares and Partial Least squares regression (https://github.com/fulepo/PLS), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2015a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Multivariate Models in Help Center and MATLAB Answers
Tags Add Tags
Open in new tab

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes
1.0.0.0

Screenshot

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.