Bound lengths based on constant-stress PALT under different censoring patterns

Prakash, Gyan; Singh, Parikshit Kishor

doi:10.14419/ijsw.v6i1.8662

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…, R m ). Recent years have seen an increase in the amount of literature on PFFC, including in [23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis and Theoretical Framework for a Partially Accelerated Life Test Model with Progressive First Failure Censoring Utilizing a Power Hazard Distribution

Abd-El-Monem,

Eliwa,

El-Morshedy

et al. 2023

Mathematics

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Monitoring life-testing trials for a product or substance often demands significant time and effort. To expedite this process, sometimes units are subjected to more severe conditions in what is known as accelerated life tests. This paper is dedicated to addressing the challenge of estimating the power hazard distribution, both in terms of point and interval estimations, during constant- stress partially accelerated life tests using progressive first failure censored samples. Three techniques are employed for this purpose: maximum likelihood, two parametric bootstraps, and Bayesian methods. These techniques yield point estimates for unknown parameters and the acceleration factor. Additionally, we construct approximate confidence intervals and highest posterior density credible intervals for both the parameters and acceleration factor. The former relies on the asymptotic distribution of maximum likelihood estimators, while the latter employs the Markov chain Monte Carlo technique and focuses on the squared error loss function. To assess the effectiveness of these estimation methods and compare the performance of their respective confidence intervals, a simulation study is conducted. Finally, we validate these inference techniques using real-life engineering data.

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“…, R m ). Recent years have seen an increase in the amount of literature on PFFC, including in [23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis and Theoretical Framework for a Partially Accelerated Life Test Model with Progressive First Failure Censoring Utilizing a Power Hazard Distribution

Abd-El-Monem,

Eliwa,

El-Morshedy

et al. 2023

Mathematics

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show abstract

“…Recently many authors have studied PALT from the Bayesian view point, such as Jaheen et al [15] and EL-Sagheer [10]. Also, few studies have considered prediction assuming PALT such as Abushal and AL-Zaydi [16] and Prakash and Singh [17].…”

Section: Introductionmentioning

confidence: 99%

Bayesian Estimation and Prediction Based on Constant Stress-Partially Accelerated Life Testing for Topp Leone-Inverted Kumaraswamy Distribution

AL-Dayian

EL-Helbawy

Refaey

et al. 2021

JAMCS

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Accelerated life testing or partially accelerated life tests is very important in life testing experiments because it saves time and cost. Partially accelerated life tests are used when the data obtained from accelerated life tests cannot be extrapolated to usual conditions. This paper proposes, constant–stress partially accelerated life test using Type II censored samples, assuming that the lifetime of items under usual condition have the Topp Leone-inverted Kumaraswamy distribution. The Bayes estimators for the parameters, acceleration factor, reliability and hazard rate function are obtained. Bayes estimators based on informative priors is derived under the balanced square error loss function as a symmetric loss function and balanced linear exponential loss function as an asymmetric loss function. Also, Bayesian prediction (point and bounds) is considered for a future observation based on Type-II censored under two samples prediction. Numerical studies are given and some interesting comparisons are presented to illustrate the theoretical results. Moreover, the results are applied to real data sets.

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Bound lengths based on constant-stress PALT under different censoring patterns

Cited by 2 publications

References 7 publications

Statistical Analysis and Theoretical Framework for a Partially Accelerated Life Test Model with Progressive First Failure Censoring Utilizing a Power Hazard Distribution

Statistical Analysis and Theoretical Framework for a Partially Accelerated Life Test Model with Progressive First Failure Censoring Utilizing a Power Hazard Distribution

Bayesian Estimation and Prediction Based on Constant Stress-Partially Accelerated Life Testing for Topp Leone-Inverted Kumaraswamy Distribution

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