Translator Disclaimer
November 2019 Bayesian inference on power Lindley distribution based on different loss functions
Abbas Pak, M. E. Ghitany, Mohammad Reza Mahmoudi
Braz. J. Probab. Stat. 33(4): 894-914 (November 2019). DOI: 10.1214/18-BJPS428


This paper focuses on Bayesian estimation of the parameters and reliability function of the power Lindley distribution by using various symmetric and asymmetric loss functions. Assuming suitable priors on the parameters, Bayes estimates are derived by using squared error, linear exponential (linex) and general entropy loss functions. Since, under these loss functions, Bayes estimates of the parameters do not have closed forms we use lindley’s approximation technique to calculate the Bayes estimates. Moreover, we obtain the Bayes estimates of the parameters using a Markov Chain Monte Carlo (MCMC) method. Simulation studies are conducted in order to evaluate the performances of the proposed estimators under the considered loss functions. Finally, analysis of a real data set is presented for illustrative purposes.


Download Citation

Abbas Pak. M. E. Ghitany. Mohammad Reza Mahmoudi. "Bayesian inference on power Lindley distribution based on different loss functions." Braz. J. Probab. Stat. 33 (4) 894 - 914, November 2019.


Received: 1 June 2017; Accepted: 1 December 2018; Published: November 2019
First available in Project Euclid: 26 August 2019

zbMATH: 07120738
MathSciNet: MR3996321
Digital Object Identifier: 10.1214/18-BJPS428

Rights: Copyright © 2019 Brazilian Statistical Association


This article is only available to subscribers.
It is not available for individual sale.

Vol.33 • No. 4 • November 2019
Back to Top