The subject of this article is to present the beta – regression model, where we assume that one parameter in the model is described as a combination of algebraically independent continuous functions. The proposed beta model is useful when the dependent variable is continuous and restricted to the bounded interval. The parameters are obtained by maximum likelihood estimation. We prove that estimators are consistent and asymptotically normal
Doubly bounded continuous data are common in the social and behavioral sciences. Examples include ju...
The consistency and asymptotic normality of the maximum likelihood estimator is established for the ...
Beta regression models are widely used for modeling continuous data limited to the unit interval, su...
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
Abstract. This paper considers a nonlinear regression model, in which the dependent variable has the...
This paper considers a nonlinear regression model, in which the dependent variable has the gamma dis...
A relevant problem in applied statistics concerns modeling rates, proportions or, more generally, co...
Abstract. In this paper, we prove that there exists exactly one maximum likelihood estimator for the...
Abstract. This paper proposes a regression model where the response is beta distributed using a para...
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical exampl...
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical exampl...
The thesis deals with a beta regression model suitable for analysing data whose range of values is t...
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical exampl...
Aim of this contribution is to propose a new regression model for continuous variables bounded to th...
Beta regression models provide an adequate approach for modeling continuous outcomes limited to the ...
Doubly bounded continuous data are common in the social and behavioral sciences. Examples include ju...
The consistency and asymptotic normality of the maximum likelihood estimator is established for the ...
Beta regression models are widely used for modeling continuous data limited to the unit interval, su...
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
Abstract. This paper considers a nonlinear regression model, in which the dependent variable has the...
This paper considers a nonlinear regression model, in which the dependent variable has the gamma dis...
A relevant problem in applied statistics concerns modeling rates, proportions or, more generally, co...
Abstract. In this paper, we prove that there exists exactly one maximum likelihood estimator for the...
Abstract. This paper proposes a regression model where the response is beta distributed using a para...
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical exampl...
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical exampl...
The thesis deals with a beta regression model suitable for analysing data whose range of values is t...
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical exampl...
Aim of this contribution is to propose a new regression model for continuous variables bounded to th...
Beta regression models provide an adequate approach for modeling continuous outcomes limited to the ...
Doubly bounded continuous data are common in the social and behavioral sciences. Examples include ju...
The consistency and asymptotic normality of the maximum likelihood estimator is established for the ...
Beta regression models are widely used for modeling continuous data limited to the unit interval, su...