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
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Quantitative estimation of soil salinity by means of different modeling methods and visible-near infrared (VIS–NIR) spectroscopy, Ebinur Lake Wetland, Northwest China
TL;DR: The Pretreatment of fractional derivative in the pretreatment of visible and near infrared (VIS–NIR) spectroscopy could be useful for monitoring multiple soil parameters with higher accuracy, which could effectively help to analyze the soil salinity.
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Comparison of Random Forest and Pipeline Pilot Naive Bayes in Prospective QSAR Predictions
TL;DR: A comparison of the ability of Pipeline Pilot Naïve Bayes (PLPNB) and random forest to make accurate predictions on 18 large, diverse in-house QSAR data sets found random forest predictions are at least as good and in many cases significantly better than those of PLPNB on the authors' data sets.
Journal ArticleDOI
Forensic body fluid identification and differentiation by Raman spectroscopy
TL;DR: In this paper, the authors combined the specificity of Raman spectroscopy with the analytical power of statistical modeling to develop a universal, confirmatory, non-destructive, approach that can be used to differentiate and identify body fluids.
Journal ArticleDOI
Dynamics of the SAR11 bacterioplankton lineage in relation to environmental conditions in the oligotrophic North Pacific subtropical gyre
TL;DR: Partial least square to latent structure projections identified environmental variables that correlate with variation in the absolute abundance of SAR11, and provided tools for developing a predictive model to explain time and depth-dependent variations in SAR11.
Journal ArticleDOI
Power Analysis and Sample Size Determination in Metabolic Phenotyping.
Benjamin J. Blaise,Gonçalo D S Correia,Adrienne Tin,J. Hunter Young,Anne-Claire Vergnaud,Matthew R. Lewis,Jake T M Pearce,Paul Elliott,Jeremy K. Nicholson,Elaine Holmes,Timothy M. D. Ebbels +10 more
TL;DR: This work introduces a new approach, based on multivariate simulation, which deals effectively with the highly correlated structure and high-dimensionality of metabolic phenotyping data, and investigates the complex relationship between sample size, power, and effect size for real multivariate data sets.
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.