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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Journal ArticleDOI
Near-infrared hyperspectral imaging and partial least squares regression for rapid and reagentless determination of Enterobacteriaceae on chicken fillets
TL;DR: It was demonstrated that hyperspectral imaging is a potential tool for determining food sanitation and detecting bacterial pathogens on food matrix without using complicated laboratory regimes.
Journal ArticleDOI
Generalizable representations of pain, cognitive control, and negative emotion in medial frontal cortex
Philip A. Kragel,Michiko Kano,Lukas Van Oudenhove,Huynh Giao Ly,Patrick Dupont,Amandine Rubio,Amandine Rubio,Chantal Delon-Martin,Chantal Delon-Martin,Bruno Bonaz,Bruno Bonaz,Stephen B. Manuck,Peter J. Gianaros,Marta Ceko,Elizabeth A. Reynolds Losin,Choong-Wan Woo,Thomas E. Nichols,Tor D. Wager +17 more
TL;DR: Assessing person-level human brain maps across 18 fMRI studies, the authors identify separable representations of pain, cognitive control, and negative emotion in the medial frontal cortex that generalize across different studies and tasks.
Journal ArticleDOI
Multivariate data analysis applied to spectroscopy: Potential application to juice and fruit quality
TL;DR: In this article, the authors highlight the different steps, methods and issues to consider when calibrations based on NIR spectra are developed for the measurement of chemical parameters in both fruits and fruit juices.
Journal ArticleDOI
Knowledge discovery in metabolomics: An overview of MS data handling
TL;DR: A broad overview of the methodologies developed to handle and process MS metabolomic data, compare the samples and highlight the relevant metabolites, starting from the raw data to the biomarker discovery is provided.
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Resistant starch alters gut microbiome and metabolomic profiles concurrent with amelioration of chronic kidney disease in rats
Dorothy A. Kieffer,Brian D. Piccolo,Nosratola D. Vaziri,Shuman Liu,Wei L. Lau,Mahyar Khazaeli,Sohrab Nazertehrani,Mary E. Moore,Maria L. Marco,Roy J. Martin,Sean H. Adams +10 more
TL;DR: Outcomes from this study were coincident with improvements in kidney function indexes and amelioration of CKD outcomes previously reported for these rats, suggesting an important role for microbial-derived factors and gut microbe metabolism in regulating host kidney function.
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.