Add to ORKGThis paper considers a nonlinear regression model, in which the dependent variable has the gamma distribution. A model is considered in which the shape parameter of the random variable is the sum of continuous and algebraically independent functions. The paper proves that there is exactly one maximum likelihood estimator for the gamma regression model
In this paper, we consider the multicollinearity problem in the gamma regression model when model pa...
The paper considers statistical inference for R = P(X \u3c Y) in the case when both X and Y have gen...
It is well-known that maximum likelihood (ML) estimators of the two parame- ters in a Gamma distribu...
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...
The subject of this article is to present the beta – regression model, where we assume that one para...
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
In this paper, we consider the problem of estimation of a regression model with both linear and nonl...
Maximum Likelihood Estimation for Gamma Distribution and its Numerical Solution by Newton-Raphson an...
In this paper, we consider the multicollinearity problem in the gamma regression model when model pa...
The paper considers statistical inference for R = P(X \u3c Y) in the case when both X and Y have gen...
It is well-known that maximum likelihood (ML) estimators of the two parame- ters in a Gamma distribu...
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...
The subject of this article is to present the beta – regression model, where we assume that one para...
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
In this paper, we consider the problem of estimation of a regression model with both linear and nonl...
Maximum Likelihood Estimation for Gamma Distribution and its Numerical Solution by Newton-Raphson an...
In this paper, we consider the multicollinearity problem in the gamma regression model when model pa...
The paper considers statistical inference for R = P(X \u3c Y) in the case when both X and Y have gen...
It is well-known that maximum likelihood (ML) estimators of the two parame- ters in a Gamma distribu...