Estimation of the Parameters of the Power Size Biased Chris-Jerry Distribution


Authors : Chidera F. Innocent; Omoruyi A. Frederick; Edidiong M. Udofia; Okechukwu J. Obulezi; Chinyere P. Igbokwe

Volume/Issue : Volume 8 - 2023, Issue 5 - May

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://bit.ly/42MUkOa

DOI : https://doi.org/10.5281/zenodo.7947382

This paper extends the one-parameter ChrisJerry distribution to the power size biased Chris-Jerry distribution, a lifetime distribution in the class of the Lindley distribution. We derive the r th moment and particularly estimated the parameters using six classical methods and the Bayesian method. Results of the two real data analyses show that the proposed PSBCJ distribution is better than the likes of Marshall-Olkin Sujatha (MOS) distribution, Two-Parameter Lindley (TPL) distribution, Kumaraswamy-Weibull (KW) distribution, ZubairExponential (ZE) distribution, Lindley Distribution (LD), Exponential Distribution (ED), Pareto (P) distribution, Lindley-Lomax (LL) distribution and Lindley-Pareto (LP) distribution. The weighted least squares is the best method for estimating the parameters of the proposed distribution since the standard errors are the least among other methods.

Keywords : Chris-Jerry Distribution, Power Size Biased Chris-Jerry Distribution, Classical Estimation, Bayesian Estimation.

CALL FOR PAPERS


Paper Submission Last Date
30 - April - 2024

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe