Objective Bayesian Analysis for the Power Function II Distribution under Doubly Type II Censored Data

Authors

  • Tabassum Naz Sindhu Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
  • Zawar Hussain Department of Statistics, Faculty of Computing, The Islamia University of Bahawalpur, Pakistan

Keywords:

Inverse transformation method, doubly censored samples, loss functions, posterior predictive distributions, credible intervals, predictive intervals

Abstract

Trimmed samples are widely utilized in several areas of statistical practice, especially when some sample values at either or both extremes might have been adulterated. In this paper, the problem of estimating the parameter of power function II distribution based on trimmed samples under informative and non-informative priors has been addressed. The problem discussed using Bayesian approach to estimate the parameter of power function II distribution. The explicit expressions for estimator and risk are developed under all loss functions. Elicitation of hyperparameter through prior predictive approach is also discussed. Posterior predictive distributions along with posterior predictive intervals and credible intervals are also derived under different priors. A comparison is made using the Monte Carlo simulation. The influence of parametric value on the estimate and risk is also discussed.

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Published

2022-06-29

Issue

Section

Articles