scispace - formally typeset
Journal ArticleDOI

PLS-regression: a basic tool of chemometrics

Reads0
Chats0
TLDR
PLS-regression (PLSR) as mentioned in this paper is the PLS approach in its simplest, and in chemistry and technology, most used form (two-block predictive PLS) is a method for relating two data matrices, X and Y, by a linear multivariate model.
About
This article is published in Chemometrics and Intelligent Laboratory Systems.The article was published on 2001-10-28. It has received 7861 citations till now. The article focuses on the topics: Partial least squares regression.

read more

Citations
More filters
Journal ArticleDOI

A tutorial review: Metabolomics and partial least squares-discriminant analysis--a marriage of convenience or a shotgun wedding.

TL;DR: This tutorial review aims to provide an introductory overview to several straightforward statistical methods such as principal component-discriminant function analysis (PC-DFA), support vector machines (SVM) and random forests (RF), which could very easily be used either to augment PLS or as alternative supervised learning methods to PLS-DA.
Journal ArticleDOI

Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.

TL;DR: A review of epidemiological literature in PubMed from January 2004 to December 2013 illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies.
Journal ArticleDOI

Partial least squares regression as an alternative to current regression methods used in ecology

TL;DR: Partial least squares regression analysis (PLSR) as mentioned in this paper is a statistical technique particularly well suited to analyzing a large array of related predictor variables (i.e. not truly independent), with a sample size not large enough compared to the number of independent variables, and in cases in which an attempt is made to approach complex phenomena or syndromes that must be defined as a combination of several variables obtained independently.
Journal ArticleDOI

Partial least squares discriminant analysis: taking the magic away

TL;DR: Partial least squares discriminant analysis (PLS-DA) has been available for nearly 20 years yet is poorly understood by most users as mentioned in this paper, however, despite these limitations, PLS-DA can provide good insight into the causes of discrimination via weights and loadings, which gives it a unique role in exploratory data analysis, for example in metabolomics via visualization of significant variables such as metabolites or spectroscopic peaks.
Journal ArticleDOI

American Gut: an Open Platform for Citizen Science Microbiome Research.

Daniel McDonald, +64 more
TL;DR: The utility of the living data resource and cross-cohort comparison is demonstrated to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education.
References
More filters
Book

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

TL;DR: In this article, the authors present a method for detecting and assessing Collinearity of observations and outliers in the context of extensions to the Wikipedia corpus, based on the concept of Influential Observations.
Book

A User's Guide to Principal Components

TL;DR: In this paper, the authors present a directory of Symbols and Definitions for PCA, as well as some classic examples of PCA applications, such as: linear models, regression PCA of predictor variables, and analysis of variance PCA for Response Variables.
Journal ArticleDOI

A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation

TL;DR: This paper reviewed the nonparametric estimation of statistical error, mainly the bias and standard error of an estimator, or the error rate of a prediction rule, at a relaxed mathematical level, omitting most proofs, regularity conditions and technical details.
Related Papers (5)