La Trobe

File(s) under permanent embargo

Preference of prior for two component mixture of Lomax distribution

journal contribution
posted on 09.08.2021, 07:22 by Ishaq BhattiIshaq Bhatti, Younis Faryal, Muhammad Aslam

Recently, El-Sherpieny et al (2020) suggested Type -II hybrid censoring method for parametric estimation of Lomax distribution (LD) without due regards being given to the choice of priors and posterior risk associated with the model. This paper fills this gap and derived the new LDmodel with minimum posterior risk for the selection of priors. It derives a closed form expression for Bayes estimates and posterior risks using Square error loss function (SELF), Weighted loss function (WLF), Quadratic loss function (QLF) and Degroot loss function (DLF). Prior predictive approach is used to elicit the hyper parameters of mixture model. Analysis of Bayes estimates and posterior risks is presented in terms of sample size (n), mixing proportion ( p ) and censoring rate ( 0 t ), with the help of simulation study. Usefulness of the model is demonstrated on applying it to simulated and real-life data which show promising results in terms of better estimation and risk reduction.


History

Publication Date

15/07/2021

Journal

Journal of Statistical Theory and Applications

Publisher

Atlantis Press

ISSN

1538-7887

Rights Statement

The Authors reserves all moral rights over the deposited text and must be credited if any re-use occurs.

Usage metrics

Categories

Licence

Exports