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...

Abstract Bayesian estimators and highest posterior density credible intervals are obtained for two popular inequality measures, viz. the Gini index Bonferroni in case of Dagum distribution. The study considers informative non-informative priors, i.e. Mukherjee-Islam prior extension Jeffrey’s prior, respectively, under presumption Linear Exponential (LINEX) loss function. A Monte Carlo simulatio...

In this paper, we consider the Bayesian estimation of parameters in the proportional hazards model of random censorship for the Weibull distribution under different asymmetric loss functions. It is well-known for the Weibull distribution that a joint conjugate prior on the parameters does not exist; we use both the informative and noninformative priors on the model parameters. Bayes estimates u...

Estimators of the reliability function in a GLM (generalized life model) are considered. The class of the GLM includes (among others) the Weibull, Pareto, Beta, Gompertz, and Rayleigh distribution. A proper general prior density and the predictive function for general class of distribution proposed by Al-Hussaini [1] are used to obtain the exact estimate. Also, the Bayes estimates relative to s...

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...

Most of estimation methods reported in the literature are based on simple random sampling (SRS), which to certain extent is considerably less effective in estimating the parameters as compared to a new sampling technique, ranked set sampling (RSS) and its modifications. In this Paper we address the problem of Bayesian estimation of the parameters for Weibull distribution, based on ranked set sa...

In this paper we develop approximate Bayes estimators of the two parameters logistic distribution. Lindley’s approximation and importance sampling techniques are applied. The Gaussian-gamma prior distribution and progressively type-II censored samples are assumed. Quadratic, linex and general entropy loss functions are used. The statistical performances of the Bayes estimates under quadratic, l...