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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Bioreactor monitoring with spectroscopy and chemometrics: a review
TL;DR: In this review, published material on the potential application of different spectroscopic techniques for bioreactor monitoring is critically discussed, with particular emphasis on optical fiber technology, reported for in situ bioprocess monitoring.
Journal ArticleDOI
High-Throughput Metabolomics by 1D NMR
Alessia Vignoli,Veronica Ghini,Gaia Meoni,Cristina Licari,Panteleimon G. Takis,Leonardo Tenori,Paola Turano,Claudio Luchinat +7 more
TL;DR: From the analytical point of view, NMR has pros and cons but does provide a peculiar holistic perspective that may speak for its future adoption as a population‐wide health screening technique.
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Source Apportionment: Findings from the U.S. Supersites Program
TL;DR: UNMIX, positive matrix factorization (PMF), and effective variance are different solutions to the chemical mass balance (CMB) receptor model equations and are implemented on available software.
Journal ArticleDOI
Catchment controls on solute export
TL;DR: In this article, the authors investigated long-term time series of stream water quality and quantity of nine neighboring catchments in Central Germany ranging from relatively pristine mountain catchments to agriculturally dominated lowland catchments, spanning large gradients in land use, geology, and climatic conditions.
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Practical guidelines for reporting results in single- and multi-component analytical calibration: A tutorial
TL;DR: Practical guidelines for reporting analytical calibration results are provided and pertinent subjects here included are the choice of algorithms, the estimation of analytical figures of merit, the use of non-linear models, the consideration of the model regression coefficients for variable selection, and the application of certain mathematical pre-processing procedures such as smoothing.
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.