In this paper we propose a new residuals for gamma regression models, assuming that both mean and shape parameters, follow regression structures. The models are summarized and fitted by applying both classic and Bayesian methods as proposed by Cepeda-Cuervo. The residuals are proposed from properties of the biparametric exponential family of distributions and simulated and real data sets are analyzed to determine the performance and behavior of the proposed residuals
This paper develops a class of density regression models based on proportional hazards family, namel...
Propor uma família de distribuição de probabilidade mais ampla e flexível é de grande importância em...
summary:Up to present for modelling and analyzing of random phenomenons, some statistical distributi...
The class of gamma regression models is based on the assumption that the dependent variable is gamma...
We propose and study a new log-gamma Weibull regression model. We obtain explicit expressions for th...
This paper introduces a new extension of the gamma distribution, named as a new extended gamma dist...
In this paper, we formulate and develop a log-linear model using a new distribution called the log-g...
In survival analysis interest lies in modeling data that describe the time to a particular event. In...
No presente trabalho, e proposto um modelo de regressão utilizando a distribuição gama generalizada ...
The gamma distribution is highly important in applications and data modeling. It is usually used to ...
summary:The bivariate gamma distribution is taken as a life test model to analyse a series system wi...
In this article, we compare three residuals based on the deviance component in generalised log-gamma...
A Gamma distributed response is subjected to regression penalized likelihood estimations of Least Ab...
This work proposes joint modeling of parameters in the biparametric exponential family, including h...
In this paper, we consider the multicollinearity problem in the gamma regression model when model pa...
This paper develops a class of density regression models based on proportional hazards family, namel...
Propor uma família de distribuição de probabilidade mais ampla e flexível é de grande importância em...
summary:Up to present for modelling and analyzing of random phenomenons, some statistical distributi...
The class of gamma regression models is based on the assumption that the dependent variable is gamma...
We propose and study a new log-gamma Weibull regression model. We obtain explicit expressions for th...
This paper introduces a new extension of the gamma distribution, named as a new extended gamma dist...
In this paper, we formulate and develop a log-linear model using a new distribution called the log-g...
In survival analysis interest lies in modeling data that describe the time to a particular event. In...
No presente trabalho, e proposto um modelo de regressão utilizando a distribuição gama generalizada ...
The gamma distribution is highly important in applications and data modeling. It is usually used to ...
summary:The bivariate gamma distribution is taken as a life test model to analyse a series system wi...
In this article, we compare three residuals based on the deviance component in generalised log-gamma...
A Gamma distributed response is subjected to regression penalized likelihood estimations of Least Ab...
This work proposes joint modeling of parameters in the biparametric exponential family, including h...
In this paper, we consider the multicollinearity problem in the gamma regression model when model pa...
This paper develops a class of density regression models based on proportional hazards family, namel...
Propor uma família de distribuição de probabilidade mais ampla e flexível é de grande importância em...
summary:Up to present for modelling and analyzing of random phenomenons, some statistical distributi...