The E-Bayesian and hierarchical Bayesian estimations for the proportional reversed hazard rate model based on record values


KIZILASLAN F.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.87, no.11, pp.2253-2273, 2017 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 87 Issue: 11
  • Publication Date: 2017
  • Doi Number: 10.1080/00949655.2017.1326118
  • Title of Journal : JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Page Numbers: pp.2253-2273

Abstract

In this paper, E-Bayesian and hierarchical Bayesian estimations of the shape parameter, when the underlying distribution belongs to the proportional reversed hazard rate model, are considered. Maximum likelihood, Bayesian and E-Bayesian estimates of the unknown parameter and reliability function are obtained based on record values. The Bayesian estimates are derived based on squared error and linear-exponential loss functions. It is pointed out that some previously obtained order relations of E-Bayesian estimates are inadequate and these results are improved. The relationship between E-Bayesian and hierarchical Bayesian estimations is obtained under the same loss functions. The comparison of the derived estimates is carried out by using Monte Carlo simulations. A real data set is analysed for an illustration of the findings.