A beta partial least squares regression model: Diagnostics and application to mining industry data

A beta partial least squares regression model: Diagnostics and application to mining industry data We propose a methodology based on partial least squares (PLS) regression models using the beta distribution, which is useful for describing data measured between zero and one. The beta PLS model parameters are estimated with the maximum likelihood method, whereas a randomized quantile residual and the generalized Cook and Mahalanobis distances are considered as diagnostic methods. A simulation study is provided for evaluating the performance of these diagnostic methods. We illustrate the methodology with real‐world mining data. The results obtained in this study based on the beta PLS model and its diagnostics may be of interest for the mining industry. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Stochastic Models in Business and Industry Wiley

A beta partial least squares regression model: Diagnostics and application to mining industry data

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Copyright © 2018 John Wiley & Sons, Ltd.
ISSN
1524-1904
eISSN
1526-4025
D.O.I.
10.1002/asmb.2278
Publisher site
See Article on Publisher Site

Abstract

We propose a methodology based on partial least squares (PLS) regression models using the beta distribution, which is useful for describing data measured between zero and one. The beta PLS model parameters are estimated with the maximum likelihood method, whereas a randomized quantile residual and the generalized Cook and Mahalanobis distances are considered as diagnostic methods. A simulation study is provided for evaluating the performance of these diagnostic methods. We illustrate the methodology with real‐world mining data. The results obtained in this study based on the beta PLS model and its diagnostics may be of interest for the mining industry.

Journal

Applied Stochastic Models in Business and IndustryWiley

Published: Jan 1, 2018

Keywords: ; ; ; ; ; ;

References

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