Bayesian inference for two populations of Lomax distribution under joint progressive Type-II censoring schemes with engineering applications

被引：1

作者：

Hasaballah, Mustafa M. ^{[1
]}

Tashkandy, Yusra A. ^{[2
]}

Balogun, Oluwafemi Samson ^{[3
]}

Bakr, Mahmoud E. ^{[2
]}

机构：

[1] Marg Higher Inst Engn & Modern Technol, Dept Basic Sci, Cairo 11721, Egypt

[2] King Saud Univ, Coll Sci, Dept Stat & Operat Res, Riyadh, Saudi Arabia

[3] Univ Eastern Finland, Dept Comp, Kuopio, Finland

来源：

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL | 2024年 / 40卷 / 08期

关键词：

Bayesian estimation; joint progressive censoring scheme; Lomax distributions; Markov chain Monte Carlo method; EXACT LIKELIHOOD INFERENCE; EXPONENTIAL POPULATIONS; RELIABILITY; BURR;

D O I：

10.1002/qre.3633

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The joint progressive Type-II censoring scheme is an advantageous cost-saving strategy. In this paper, investigated classical and Bayesian methodologies for estimating the combined parameters of two distinct Lomax distributions employing the joint progressive Type-II censoring scheme. Maximum likelihood estimators have been derived, and asymptotic confidence intervals are presented. Bayesian estimates and their corresponding credible intervals are calculated, incorporating both symmetry and asymmetry loss functions through the utilization of the Markov Chain Monte Carlo (MCMC) method. The simulation aspect has employed the MCMC approximation method. Furthermore, discussed the practical application of these methods, providing illustration through the analysis of a real dataset.

引用

页码：4335 / 4351

页数：17

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