Inference for Parameters of Exponential Distribution under Combined Type II Progressive Hybrid Censoring Scheme

Kyeongjun Lee ()
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Kyeongjun Lee: Department of Mathematics and Big Data Science, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea

Mathematics, 2024, vol. 12, issue 6, 1-23

Abstract: In recent years, various forms of progressive hybrid censoring schemes (PHCS) have gained significant traction in survival and reliability analysis studies due to their versatility. However, these PHCS variants are often characterized by complexity stemming from the multitude of parameters involved in their specification. Consequently, the primary objective of this paper is to propose a unified approach termed combined type II progressive hybrid censoring scheme ( ComT 2 PHCS) capable of encompassing several existing PHCS variations. Our analysis focuses specifically on the exponential distribution (ExDist). Bayesian inference techniques are employed to estimate the parameters of the ExDist under the ComT 2 PHCS. Additionally, we conduct fundamental distributional analyses and likelihood inference procedures. We derive the conditional moment-generating function (CondMGF) of maximum likelihood estimator (MLE) for parameters of the ExDist under ComT 2 PHCS. Further, we use CondMGF for the distribution of MLE for parameters of ExDist under ComT 2 PHCS. Finally, we provide an illustrative example to elucidate the inference methods derived in this paper.

Keywords: Bayesian inference; combined type II progressive hybrid censoring; maximum likelihood estimator; moment-generating function (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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