Exact Likelihood Inference for an Exponential Parameter under Generalized Adaptive Progressive Hybrid Censoring

Lee, Hyojin; Lee, Kyeong‐Jun

doi:10.3390/sym12071149

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…Recently, some studies on PHCS have been carried out by many authors (Refs. [6][7][8][9][10][11][12][13][14][15][16][17][18][19]). Ref.…”

Section: Introductionmentioning

confidence: 99%

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

Lee

2024

Mathematics

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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 (ComT2PHCS) 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 ComT2PHCS. 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 ComT2PHCS. Further, we use CondMGF for the distribution of MLE for parameters of ExDist under ComT2PHCS. Finally, we provide an illustrative example to elucidate the inference methods derived in this paper.

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“…Recently, some studies on PHCS have been carried out by many authors (Refs. [6][7][8][9][10][11][12][13][14][15][16][17][18][19]). Ref.…”

Section: Introductionmentioning

confidence: 99%

“…Ref. [6] investigated exact likelihood inference for an exponential parameter under adaptive GenT 1 PHCS. Ref.…”

Section: Introductionmentioning

confidence: 99%

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

Lee

2024

Mathematics

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“…Therefore, progressive type II censoring scheme (PrTy2CS) has become popular censoring scheme in a survival and reliability analysis problem (Refs. [1][2][3][4][5]). Though the PrTy2CS assure a number of observed failures, it has the drawback that it might take a long time to terminate the test and to observe a pre-fixed number of failures.…”

Section: Introductionmentioning

confidence: 99%

Exact Likelihood Inference for a Competing Risks Model with Generalized Type II Progressive Hybrid Censored Exponential Data

Cho

Lee

2021

Symmetry

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In many situations of survival and reliability test, the withdrawal of units from the test is pre-planned in order to to free up testing facilities for other tests, or to save cost and time. It is known that several risk factors (RiFs) compete for the immediate failure cause of items. In this paper, we derive an inference for a competing risks model (CompRiM) with a generalized type II progressive hybrid censoring scheme (GeTy2PrHCS). We derive the conditional moment generating functions (CondMgfs), distributions and confidence interval (ConfI) of the scale parameters of exponential distribution (ExDist) under GeTy2PrHCS with CompRiM. A real data set is analysed to illustrate the validity of the method developed here. From the data, it can be seen that the conditional PDFs of MLEs is almost symmetrical.

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“…Although Pr2CS and Ad1PHCS assure a pre-assigned number of failures, they have the drawback that it might take a long time to observe a pre-assigned number of failures and terminate the test. For this reason, Author1 [12] suggested a GeAdPHCS in which the test is assured to end at a pre-assigned time. The survival test based on the GeAdPHCS can save both the total time and cost on tests.…”

Section: Introductionmentioning

confidence: 99%

Exact Inference for an Exponential Parameter under Generalized Adaptive Progressive Hybrid Censored Competing Risks Data

Cho

Lee

2020

Symmetry

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It is known that the lifetimes of items may not be recorded exactly. In addition, it is known that more than one risk factor (RisF) may be present at the same time. In this paper, we discuss exact likelihood inference for competing risk model (CoRiM) with generalized adaptive progressive hybrid censored exponential data. We derive the conditional moment generating function (ConMGF) of the maximum likelihood estimators of scale parameters of exponential distribution (ExpD) and the resulting lower confidence bound under generalized adaptive progressive hybrid censoring scheme (GeAdPHCS). From the example data, it can be seen that the PDF of MLE is almost symmetrical.

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Exact Likelihood Inference for an Exponential Parameter under Generalized Adaptive Progressive Hybrid Censoring

Cited by 4 publications

References 18 publications

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

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

Exact Likelihood Inference for a Competing Risks Model with Generalized Type II Progressive Hybrid Censored Exponential Data

Exact Inference for an Exponential Parameter under Generalized Adaptive Progressive Hybrid Censored Competing Risks Data

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