Statistical Inference for the Gompertz Distribution Based on Adaptive Type-II Progressive Censoring Scheme
M. M. Amein,
M. El-Saady,
M. M. Shrahili,
A. R. Shafay and
Sanku Dey
Mathematical Problems in Engineering, 2022, vol. 2022, 1-11
Abstract:
The topic of estimating the parameters of Gompertz distribution using an adaptive Type-II progressively censored data are described in this paper. The unknown parameters, the reliability, and the hazard functions are estimated using maximum likelihood and Bayesian estimation methods. The approximate confidence intervals of them are then determined. Furthermore, the Markov chain Monte Carlo approach is used to perform a Bayesian estimate procedure and compute the credible intervals. Finally, a Monte Carlo simulation study is done to assess the performance of the two estimating methods, and a numerical example with real data is shown to demonstrate the procedures’ utility.
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/1266384.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/1266384.xml (application/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1266384
DOI: 10.1155/2022/1266384
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().