Browsing by Author "260999fd-79b7-4710-abf0-e9b65b41df0b"
Now showing items 1-5 of 5
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A beta partial least squares regression model: Diagnostics and application to mining industry data
Huerta, Mauricio; Leiva, Víctor; Lillo, Camilo; Rodríguez-Gallardo, Marcelo (2018)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 ...
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On a partial least squares regression model for asymmetric data with a chemical application in mining
Huerta, Mauricio; Leiva, Víctor; Liu, Shuangzhe; Rodríguez-Gallardo, Marcelo; Villegas, Danny (2019)In chemometrical applications, covariates in regression models are often correlated, causing a collinearity problem that can be solved by partial least squares (PLS) regression. In addition, high dimensionality in the space ...
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On some goodness-of-fit tests and their connection to graphical methods with uncensored and censored data
Castro-Kuriss, Claudia; Huerta, Mauricio; Leiva, Víctor; Tapia, Alejandra (2020)In this work, we present goodness-of-fit tests related to the Kolmogorov-Smirnov and Michael statistics and connect them to graphical methods with uncensored and censored data. The Anderson-Darling test is often empirically ...
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Partial least squares models and their formulations, diagnostics and applications to spectroscopy
Huerta, Mauricio; Leiva, Víctor; Marchant-Fuentes, Carolina; Rodríguez-Gallardo, Marcelo (2020)Partial least squares (PLS) models are a multivariate technique developed to solve the problem of multicollinearity and/or high dimensionality related to explanatory variables in multiple linear models. PLS models have ...
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Partial least squares models and their formulations, diagnostics and applications to spectroscopy
Huerta, Mauricio; Leiva, Víctor; Marchant-Fuentes, Carolina; Rodríguez-Gallardo, Marcelo (2020)Partial least squares (PLS) models are a multivariate technique developed to solve the problem of multicollinearity and/or high dimensionality related to explanatory variables in multiple linear models. PLS models have ...