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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The evolution of partial least squares models and related chemometric approaches in metabonomics and metabolic phenotyping
Judith M. Fonville,Selena E. Richards,Richard H. Barton,Claire L. Boulangé,Timothy M. D. Ebbels,Jeremy K. Nicholson,Elaine Holmes,Marc-Emmanuel Dumas +7 more
TL;DR: This review discusses techniques that have evolved from principal component analysis and partial least squares methods with a focus on improved interpretation and modeling with respect to biomarker recovery and data visualization in the context of metabonomic applications.
Journal ArticleDOI
Influence of facial skin attributes on the perceived age of Caucasian women.
Alex Nkengne,Christiane Bertin,Georgios N. Stamatas,A Giron,A Giron,Ana B. Rossi,Nathalie Issachar,Bernard Fertil +7 more
TL;DR: This study assesses the contribution of individual skin attributes of the face on the perceived age of Caucasian women to assess the influence of age and gender of graders with regard to the age perception.
Journal ArticleDOI
Metabolomics for bioactivity assessment of natural products
TL;DR: The description of some examples of successful metabolomics applications in several important fields related to drug discovery from natural sources aims at raising the potential of metabolomics in reducing the gap between natural products (NP) and modern drug discovery demand.
Journal ArticleDOI
Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy
Shawn P. Serbin,Aditya Singh,Ankur R. Desai,Sean DuBois,Andrew D. Jablonski,Clayton C. Kingdon,Eric L. Kruger,Philip A. Townsend +7 more
TL;DR: In this article, a partial least squares regression (PLSR) model was employed to characterize the pixel-level variation in canopy V cmax (at a standardized canopy temperature of 30°C) and its sensitivity to temperature (E V ) at the canopy scale.
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Linear and nonlinear modeling approaches for urban air quality prediction
TL;DR: The sensitivity analysis performed to evaluate the importance of the input variables in optimal GRNN revealed that SO(2) was the most influencing parameter in RSPM model, whereas, SPM was theMost important input variable in other two models.
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.