Journal ArticleDOI
PLS-regression: a basic tool of chemometrics
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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
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Combination of spectra and texture data of hyperspectral imaging for prediction of pH in salted meat
TL;DR: Methods of combining spectral with texture analyses are effective for improving meat quality prediction by predicting pH based on spectral, textural or combined data.
Journal ArticleDOI
QSAR modeling of toxicity of diverse organic chemicals to Daphnia magna using 2D and 3D descriptors.
Supratik Kar,Kunal Roy +1 more
TL;DR: The PLS model suggests that higher lipophilicity and electrophilicity, less negative charge surface area and presence of ether linkage, hydrogen bond donor groups and acetylenic carbons are responsible for greater toxicity of chemicals.
Journal ArticleDOI
Bioelectronic tongues: New trends and applications in water and food analysis
TL;DR: The capabilities of bioelectronic tongues as analytical tools, especially suited for screening analysis, with particular emphasis in water analysis and the characterization of food and beverages are illustrated.
REVIEW: New frontiers in metabolomics: from measurement to insight
Eli Riekeberg,Robert Powers +1 more
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Impact of multicollinearity on small sample hydrologic regression models
Charles N. Kroll,Peter Song +1 more
TL;DR: In this article, a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS).
References
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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
Bradley Efron,Gail Gong +1 more
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.