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A beta partial least squares regression model: Diagnostics and application to mining industry data
(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 ...
A Cobb–Douglas type model with stochastic restrictions: Formulation, local influence diagnostics and data analytics in economics
(2019)
We propose a methodology for modelling and influence diagnostics in a Cobb–Douglas type setting. This methodology is useful for describing case-studies from economics. We consider stochastic restrictions for the model based ...
Monitoring urban environmental pollution by bivariate control charts: New methodology and case study in Santiago, Chile
(2019)
Particulate matter (PM) pollution is a serious environmental problem. Santiago of Chile is one of the most polluted cities in the world in terms of PM2.5 and PM10. Monitoring of environmental risk is useful for detecting ...
On a partial least squares regression model for asymmetric data with a chemical application in mining
(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 ...
Robust multivariate control charts based on Birnbaum–Saunders distributions
(2018)
Multivariate control charts are powerful and simple visual tools for monitoring the quality of a process. This multivariate monitoring is carried out by considering simultaneously several correlated quality characteristics ...
Multivariate Birnbaum-Saunders distributions: modelling and applications
(2018)
Since its origins and numerous applications in material science, the Birnbaum–Saunders family of distributions has now found widespread uses in some areas of the applied sciences such as agriculture, environment and medicine, ...