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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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NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

Kerry Cawse-Nicholson, +66 more
TL;DR: The 2017-2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a "designated targeted observable" (DO) as discussed by the authors.
Journal ArticleDOI

High-throughput manufacturing of size-tuned liposomes by a new microfluidics method using enhanced statistical tools for characterization

TL;DR: This study demonstrates microfluidics as a robust and high-throughput method for the scalable and highly reproducible manufacture of size-controlled liposomes and the application of statistically based process control increases understanding and allows for the generation of a design-space for controlled particle characteristics.
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UPLC-ESI-QTOF/MS and multivariate data analysis for blood plasma and serum metabolomics: effect of experimental artefacts and anticoagulant

TL;DR: Hemparin plasma or serum should be the order of best choice for LC-ESI/MS-based metabolomics research and Citrate and EDTA should be avoided since interferences and serious matrix effects were encountered on some co-eluting polar metabolites.
Book

Model-Based Clustering and Classification for Data Science

TL;DR: In this paper, the authors frame cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions, such as how many clusters are there? which method should I use? How should I handle outliers.
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MixMC: A Multivariate Statistical Framework to Gain Insight into Microbial Communities.

TL;DR: MixMC as discussed by the authors is a multivariate data analysis framework for metagenomic biomarker discovery, which accounts for the compositional nature of 16S data and enables detection of subtle differences when high inter-subject variability is present due to microbial sampling performed repeatedly on the same subjects, but in multiple habitats.
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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