In this paper, we propose a simple parametric modal linear regression model where the
response variable is gamma distributed using a new parameterization of this distribution that …

Modal regression is an alternative approach for investigating the relationship between the
most likely response and covariates and can hence reveal important structure missed by …

Compared to mean regression and quantile regression, the literature on modal regression is
very sparse. A unifying framework for Bayesian modal regression is proposed, based on a …

An inference procedure is proposed to provide consistent estimators of parameters in a
modal regression model with a covariate prone to measurement error. A score‐based …

Neste trabalho é desenvolvido um estudo fundamentado na distribuição Weibull truncada.
O truncamento é realizado no intervalo (0, 2), denominado truncamento à direita. No …

This dissertation considers statistical inference methods for parametric modal regression
models. In Chapter 1, we motivate the mode as the measure of central tendency instead of …

A classe de modelos de regressão beta é usada para modelar variáveis respostas no
intervalo (0, 1), como taxas e proporções. Ferrari e Cribari-Neto (2004) propuseram um …

Abstract Since the World Health Organization (WHO) Declared COVID-19 a Pandemic on
March 11, 2020 the United States'(US) economy faced unprecedented challenges; and …

Dependence on car use generates adverse effects on the sustainability of our urban
environment due to air and noise pollution and global warming. Along with technological …

Dependence on car use generates adverse effects on the sustainability of our urban
environment due to air and noise pollution and global warming. Along with technological …