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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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...