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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Linear and nonlinear modeling for simultaneous prediction of dissolved oxygen and biochemical oxygen demand of the surface water — A case study
TL;DR: In this article, partial least squares (PLS2) regression and feed forward back propagation artificial neural networks (FFBP ANNs) were applied to predict the dissolved oxygen (DO) and biochemical oxygen demand (BOD) levels in the river water using the set of independent measured variables.
Journal ArticleDOI
Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics.
Ying Guo,Yongnian Ni,Serge Kokot +2 more
TL;DR: NIR spectroscopy in conjunction with chemometrics, is a very useful and rapid technique for the discrimination of jujube fruit.
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Chilling and heat requirements for flowering in temperate fruit trees
TL;DR: It does not seem likely that reductions in chill will have a major effect on the studied species in Beijing in the near future, but over the past 50 years, heat accumulation during tree dormancy increased significantly, while chill accumulation remained relatively stable for both species.
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Hyperspectral analysis of mangrove foliar chemistry using PLSR and support vector regression
TL;DR: In this paper, the results indicated that nitrogen could be successfully modelled at the landscape level R ² ǫ = 0.67, root mean square error RMSE nRMSE Ã Ã 0.17, normalized RMSE NRMSE Ò 0.15%, whereas estimations of P, K, Ca, Mg, and Na were less encouraging.
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Optimization of pulsed thermography inspection by partial least-squares regression
TL;DR: In this paper, a statistical correlation method for the optimization of the pulsed thermography inspection is proposed, based on partial least squares regression, which decomposes the thermographic PT data sequence obtained during the cooling regime into a set of latent variables.
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.