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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.
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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.

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Advances in downstream processing of biologics – Spectroscopy: An emerging process analytical technology

TL;DR: An introduction into the field of spectroscopic tools for PAT in downstream processing (DSP) is given and recent advances and future perspectives will be reviewed.
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Comparing methods for metabolic network analysis and an application to metabolic engineering

TL;DR: The progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization are summarized.
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Advantage of Using Decorrelated Residuals in Dynamic Principal Component Analysis for Monitoring Large-Scale Systems

TL;DR: In this paper, a new methodology is proposed for monitoring multi-and megavariate systems whose variables present significant levels of autocorrelation, and new monitoring statistics are derived after the prelim...
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Physical fitness level is reflected by alterations in the human plasma metabolome.

TL;DR: It is hypothesized that high fitness status induces an increased cardiorespiratory inflammatory and antioxidant defense system, more prone to deal with the inflammatory response following exercise and nutrition intake.
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‘Rocha’ pear firmness predicted by a Vis/NIR segmented model

TL;DR: In this paper, a segmented partial least squares (PLS) prediction model for firmness of Rocha pear (Pyrus communis L.) during fruit ripening under shelf-life conditions was presented.
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.
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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.
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