Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7561994 | Chemometrics and Intelligent Laboratory Systems | 2018 | 32 Pages |
Abstract
Partial least squares (PLS) have gained wide applications especially in chemometrics, metabolomics/metabonomics as well as bioinformatics. Here, we present libPLS, a library that integrates not only basic PLS modeling algorithms but also advanced and/or recently developed methods on model assessment, outlier detection, and variable selection. This package is featured in a set of Model Population Analysis (MPA)-type approaches that have not been integrated into a single package yet and thus functionally complement existing toolboxes. libPLS provides an integrated platform for developing PLS regression and/or linear discriminant analysis (PLS-LDA) models. It is written in MATLAB and freely available at www.libpls.net.
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Hong-Dong Li, Qing-Song Xu, Yi-Zeng Liang,