The paper considers statistical inference for R = P(X \u3c Y) in the case when both X and Y have generalized gamma distributions. The maximum likelihood estimators for R are developed in the case when either all three parameters of the generalized gamma distributions are unknown or when the shape parameters are known. In addition, objective Bayes estimators based on non informative priors are constructed when the shape parameters are known. Finally, the uniform minimum variance unbiased estimators (UMVUE) are derived in the case when only the scale parameters are unknown
Abstract: In this paper,the estimation of stress-strength parameter R = P (Y<X) is considered Whe...
This paper considers a nonlinear regression model, in which the dependent variable has the gamma dis...
In this paper, some structural properties of Generalized Gamma Distribution (GGD) have been establis...
In this paper, we considered the estimation of R=P(Y<X), dubbed asStress-Strength Model (SSM), in...
In this paper, we considered the estimation of R=P(Y<X), dubbed asStress-Strength Model (SSM), in...
The problem of estimation of an unknown shape parameter under the sample drawn from the gamma distr...
The problem of estimation of an unknown shape parameter under the sample drawn from the gamma distr...
It is well-known that maximum likelihood (ML) estimators of the two parame- ters in a Gamma distribu...
In this paper, the estimation of R = P [Y \u3c X], namely Stress- Strength model is studied when bot...
In this paper, the estimation of the stress-strength parameter R = P(Y < X), when X and Y are indepe...
This paper deals with the problem of classical and Bayesian estimation of stress-strength reliabilit...
In this paper, we propose to obtain Bayesian estimators of unknown parameters of a three parameter g...
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 papers presents the comparison between maximum likelihood estimator(MLE) and Bayes estimator of...
Abstract: In this paper,the estimation of stress-strength parameter R = P (Y<X) is considered Whe...
This paper considers a nonlinear regression model, in which the dependent variable has the gamma dis...
In this paper, some structural properties of Generalized Gamma Distribution (GGD) have been establis...
In this paper, we considered the estimation of R=P(Y<X), dubbed asStress-Strength Model (SSM), in...
In this paper, we considered the estimation of R=P(Y<X), dubbed asStress-Strength Model (SSM), in...
The problem of estimation of an unknown shape parameter under the sample drawn from the gamma distr...
The problem of estimation of an unknown shape parameter under the sample drawn from the gamma distr...
It is well-known that maximum likelihood (ML) estimators of the two parame- ters in a Gamma distribu...
In this paper, the estimation of R = P [Y \u3c X], namely Stress- Strength model is studied when bot...
In this paper, the estimation of the stress-strength parameter R = P(Y < X), when X and Y are indepe...
This paper deals with the problem of classical and Bayesian estimation of stress-strength reliabilit...
In this paper, we propose to obtain Bayesian estimators of unknown parameters of a three parameter g...
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 papers presents the comparison between maximum likelihood estimator(MLE) and Bayes estimator of...
Abstract: In this paper,the estimation of stress-strength parameter R = P (Y<X) is considered Whe...
This paper considers a nonlinear regression model, in which the dependent variable has the gamma dis...
In this paper, some structural properties of Generalized Gamma Distribution (GGD) have been establis...