Bayes and classical estimators have been obtained for two-parameter exponentiated-Weibull distribution when sample is available from type-II censoring scheme. Bayes estimators have been developed under squared error loss function as well as under LINEX loss function using non-informative type of priors for the parameters. Besides, the generalized maximum likelihood estimators and the usual maxi...

In this paper, the problem of Bayesian estimation of flood quantiles is studied. Bayes estimators of the optimal dyke height under symmetric and asymmetric loss are investigated when the annual maximum sea water levels are exponentially distributed with unknown value of the mean. Three types of loss functions are considered: (i) linear loss, (ii) squared-error loss, and (iii) linex loss. In ord...

Based on progressively Type-II censored samples, the maximum likelihood and Bayes estimators for the scale parameter, reliability and cumulative hazard functions are derived. The Bayes estimators are studied under symmetric (squared error) loss function and asymmetric (LINEX and general entropy) loss functions. Tow techniques are used for computing the Bayes estimates; standard Bayes and import...

In the present article, some shrinkage testimators for the scale parameter of a two – parameter Weibull life testing model have been suggested under the LINEX loss function assuming the shape parameter is to be known. The comparisons of the proposed testimators have been made with the improved estimator.

In this paper, given a progressively type II censored sample from a generalized half logistic distribution, the Bayesian estimators are obtained under asymmetric loss functions such as LINEX loss function, Precautionary loss function, Entropy loss function for the parameter, Reliability and cumulative hazard functions. Comparisons of these estimators are made through simulation studies. Mathema...

It is now well recognized that the use of the squared error loss function (SELF) in Bayesian estimation may not be appropriate when positive and negative errors have different consequences. To overcome this difficulty, Varian (1975) and Zellner (1986) proposed an asymmetric loss function known as the LINEX loss function (LLF) and its invariant form (Basu & Ebrahimi, 1991) for any parameter θ is...

The improved estimator of the variance in the general linear model is presented under an asymmetric linex loss function.

The use of the Pareto distribution as a model for various socio-economic phenomena dates back to the late nineteenth century. In this paper, after some necessary preliminary results we deal with Bayes estimation of some of the parameters of interest under an asymmetric LINEX loss function, using suitable choice of priors when the scale parameter is known and unknown. Results of a Monte C...