Add to ORKGAbstract. 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
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...
<div><p></p><p>Regression analysis with a bounded outcome is a common problem in applied statistics....
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
The subject of this article is to present the beta – regression model, where we assume that one para...
Abstract. This paper considers a nonlinear regression model, in which the dependent variable has the...
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...
Abstract. In this paper, we prove that there exists exactly one maximum likelihood estimator for the...
A relevant problem in applied statistics concerns modeling rates, proportions or, more generally, co...
A relevant problem in applied statistics concerns modeling rates, proportions or, more generally, c...
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...
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...
Aim of this contribution is to propose a new regression model for continuous variables bounded to th...
<div><p></p><p>Regression analysis with a bounded outcome is a common problem in applied statistics....
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
The subject of this article is to present the beta – regression model, where we assume that one para...
Abstract. This paper considers a nonlinear regression model, in which the dependent variable has the...
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...
Abstract. In this paper, we prove that there exists exactly one maximum likelihood estimator for the...
A relevant problem in applied statistics concerns modeling rates, proportions or, more generally, co...
A relevant problem in applied statistics concerns modeling rates, proportions or, more generally, c...
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...
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...
Aim of this contribution is to propose a new regression model for continuous variables bounded to th...
<div><p></p><p>Regression analysis with a bounded outcome is a common problem in applied statistics....