Listar Producción Académica por materia "R software"
Mostrando publicaciones 1-14 de 14
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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 ...
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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 ...
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A family of skew-normal distributions for modeling proportions and rates with zeros/ones excess
(2020)In this paper, we consider skew-normal distributions for constructing new a distribution which allows us to model proportions and rates with zero/one inflation as an alternative to the inflated beta distributions. The new ...
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A new quantile regression model and its diagnostic analytics for a weibull distributed response with applications
(2021)Standard regression models focus on the mean response based on covariates. Quantile regression describes the quantile for a response conditioned to values of covariates. The relevance of quantile regression is even greater ...
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Birnbaum–Saunders regression models: a comparative evaluation of three approaches
(2020)This study investigates three regression models based on the Birnbaum–Saunders distribution. The first model is obtained directly through the Birnbaum–Saunders distribution; the second model is obtained via a logarithmic ...
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Data-influence analytics in predictive models applied to asthma disease
(2020)Asthma is one of the most common chronic diseases around the world and represents a serious problem in human health. Predictive models have become important in medical sciences because they provide valuable information for ...
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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 ...
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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, ...
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On a logistic regression model with random intercept: diagnostic analytics, simulation and biological application
(2020)This article proposes a methodology for diagnostics in a logistic regression with random intercept motivated by a biological study. The methodology includes local and global influence techniques allowing us to contrast the ...
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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 ...
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Partial least squares models and their formulations, diagnostics and applications to spectroscopy
(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
(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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Predicting PM2.5 and PM10 levels during critical episodes management in Santiago, Chile, with a bivariate Birnbaum-Saunders log-linear model
(2021)Improving air quality is an important environmental challenge of our time. Chile currently has one of the most stable and emerging economies in Latin America, where human impact on natural resources and air quality does ...
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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 ...