Classical and Bayesian estimation for Gompertz distribution under the unified hybrid censored sampling with application-Reference-Cited by-同舟云学术

Classical and Bayesian estimation for Gompertz distribution under the unified hybrid censored sampling with application

Published:2023-11-01 Issue:11 Volume:13 Page:
ISSN:2158-3226
Container-title:AIP Advances
language:en
Short-container-title:

Author:

Abo-Kasem O. E.¹^ORCID,Abdelgaffar A.¹^ORCID,Al Mutairi Aned²^ORCID,Khashab Rana H.³^ORCID,Abu El Azm Wael S.¹^ORCID

Affiliation:

1. Department of Statistics, Faculty of Commerce, Zagazig University 1 , Zagazig 44519, Egypt

2. Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University 2 , P.O. Box 84428, Riyadh 11671, Saudi Arabia

3. 3 Mathematics Department, Faculty of Sciences, Umm Al-Qura University, Makkah, Saudi Arabia

Abstract

This study discusses the Gompertz distribution’s statistical inference using unified hybrid censored data. Under various loss functions, the maximum likelihood and Bayesian approaches are explored for estimating the parameters for the Gompertz distribution. To compare the suggested methodologies, the Monte Carlo simulation is used, which also introduces the simulation research. By examining a genuine dataset, the applicability of the presented inference in practice is finally demonstrated.

Funder

Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

https://pubs.aip.org/aip/adv/article-pdf/doi/10.1063/5.0174543/18203223/115206_1_5.0174543.pdf

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