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
Soil salt content estimation in the Yellow River delta with satellite hyperspectral data
TL;DR: In this article, partial least squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model for soil salinization.
Journal ArticleDOI
Visible/near-infrared hyperspectral imaging prediction of textural firmness of grass carp (Ctenopharyngodon idella) as affected by frozen storage
TL;DR: In this article, the potential of using visible and near-infrared hyperspectral imaging (400-1000nm) for non-destructive prediction of firmness quality of grass carp fillet as affected by frozen storage was investigated.
Journal ArticleDOI
Partial least squares and artificial neural networks modeling for predicting chlorophenol removal from aqueous solution
TL;DR: Linear and nonlinear partial least squares regression and three-layer feed-forward artificial neural network (ANN) models were constructed to predict the removal efficiency (RE%) of the coconut fibers carbon (FC) for 2-chlorophenol (2-CP) from aqueous solutions based on 800 experimental sets obtained in a laboratory batch study as discussed by the authors.
Book ChapterDOI
Applicability Domain: A Step Toward Confident Predictions and Decidability for QSAR Modeling.
TL;DR: This chapter has attempted to summarize in this chapter the important concepts of AD including particulars of the available methods to compute the AD along with their thresholds and criteria for estimating AD through training set interpolation in the descriptor space.
Journal ArticleDOI
Forest ageing: An unexpected driver of beech leaf litter quality variability in European forests with strong consequences on soil processes
TL;DR: The role of forest age as a potential driver of intraspecific variation in leaf litter quality, that is a key plant trait determining ecosystem functioning, has largely been neglected.
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.