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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Molecular phenotyping of a UK population: defining the human serum metabolome.
Warwick B. Dunn,Wanchang Lin,Wanchang Lin,David Broadhurst,David Broadhurst,Paul Begley,Paul Begley,Marie Brown,Marie Brown,Eva Zelena,Andrew A. Vaughan,Antony Halsall,Nadine Harding,Joshua Knowles,Sue Francis-McIntyre,Andy Tseng,David I. Ellis,Steve O'Hagan,Gill Aarons,Boben Benjamin,Stephen Chew-Graham,Carly Moseley,Paula Potter,Catherine L. Winder,Catherine Potts,Paula Thornton,Catriona McWhirter,Mohammed Zubair,Martin Pan,Alistair Burns,J. Kennedy Cruickshank,J. Kennedy Cruickshank,Gordon C Jayson,Nitin Purandare,Frederick C. W. Wu,J. D. Finn,John N. Haselden,Andrew W. Nicholls,Ian D. Wilson,Ian D. Wilson,Royston Goodacre,Douglas B. Kell +41 more
TL;DR: The Husermet study as discussed by the authors used a large scale and non-targeted chromatographic MS-based metabolomics study, using samples from over 1,000 individuals, to provide a comprehensive measurement of their serum metabolomes.
Journal ArticleDOI
Potential of field hyperspectral imaging as a non destructive method to assess leaf nitrogen content in Wheat
TL;DR: In this article, the authors proposed a non-destructive method based on leaf optical properties for a nondestructive diagnosis to replace Nitrogen Nutrition Index which is a costly and destructive method.
Journal ArticleDOI
Impact of spatial soil and climate input data aggregation on regional yield simulations
Holger Hoffmann,Gang Zhao,Senthold Asseng,Marco Bindi,Christian Biernath,Julie Constantin,Elsa Coucheney,Rene Dechow,Luca Doro,Henrik Eckersten,Thomas Gaiser,Balázs Grosz,Florian Heinlein,Belay T. Kassie,Kurt Christian Kersebaum,Christian Klein,Matthias Kuhnert,Elisabet Lewan,Marco Moriondo,Claas Nendel,Eckart Priesack,Helene Raynal,Pier Paolo Roggero,Reimund P. Rötter,Stefan Siebert,Xenia Specka,Fulu Tao,Edmar Teixeira,Giacomo Trombi,Daniel Wallach,Lutz Weihermüller,Jagadeesh Yeluripati,Frank Ewert +32 more
TL;DR: The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields, and distinct error patterns indicate that the rMAE may be estimated from few soil variables.
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The EnMAP-Box—A Toolbox and Application Programming Interface for EnMAP Data Processing
Sebastian van der Linden,Andreas Rabe,Matthias Held,Benjamin Jakimow,Pedro J. Leitão,Akpona Okujeni,Marcel Schwieder,Stefan Suess,Patrick Hostert +8 more
TL;DR: An overview of the EnMAP-Box is given, typical workflows along an application example are explained, and the concept for making it a frequently used and constantly extended platform for imaging spectroscopy applications is exemplified.
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PCA and PLS with very large data sets
TL;DR: A multivariate approach based on projections—PCA and PLS—was introduced to cope with the rapidly increasing volumes of data produced in chemical laboratories and showed promising results.
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.