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<p>This study focuses on estimating reliability for the Weibull distribution | <p>This study focuses on estimating reliability for the Weibull distribution | ||
within the framework of constant-stress partially accelerated life tests, | within the framework of constant-stress partially accelerated life tests, | ||
| − | incorporating the | + | incorporating the unified Type-I progressive hybrid censoring scheme |
that has not been previously examined. The unknown parameters of the | that has not been previously examined. The unknown parameters of the | ||
Weibull model, including acceleration factors and key reliability measures | Weibull model, including acceleration factors and key reliability measures | ||
such as the reliability function and hazard rate function under normal use | such as the reliability function and hazard rate function under normal use | ||
| − | conditions, are estimated. | + | conditions, are estimated. The maximum likelihood method is used to |
| − | obtain point estimates and approximate | + | obtain point estimates and approximate confidence intervals. Additionally, a Bayesian approach based on Markov Chain Monte Carlo sampling |
is applied to compute point estimates and Bayesian credible intervals, | is applied to compute point estimates and Bayesian credible intervals, | ||
assuming a squared error loss function. A simulation study is conducted | assuming a squared error loss function. A simulation study is conducted | ||
to compare the performance of the estimators using criteria such as mean | to compare the performance of the estimators using criteria such as mean | ||
| − | squared error, interval width, and coverage probability. Finally, two | + | squared error, interval width, and coverage probability. Finally, two real-world data sets from accelerated life testing are analyzed to illustrate the |
practical usefulness of the proposed methods.</p> | practical usefulness of the proposed methods.</p> | ||
== Document == | == Document == | ||
<pdf>Media:Review_361464043566_4672_149. TSP_RIMNI_79283.pdf</pdf> | <pdf>Media:Review_361464043566_4672_149. TSP_RIMNI_79283.pdf</pdf> | ||
Latest revision as of 12:47, 25 September 2026
Abstract
This study focuses on estimating reliability for the Weibull distribution within the framework of constant-stress partially accelerated life tests, incorporating the unified Type-I progressive hybrid censoring scheme that has not been previously examined. The unknown parameters of the Weibull model, including acceleration factors and key reliability measures such as the reliability function and hazard rate function under normal use conditions, are estimated. The maximum likelihood method is used to obtain point estimates and approximate confidence intervals. Additionally, a Bayesian approach based on Markov Chain Monte Carlo sampling is applied to compute point estimates and Bayesian credible intervals, assuming a squared error loss function. A simulation study is conducted to compare the performance of the estimators using criteria such as mean squared error, interval width, and coverage probability. Finally, two real-world data sets from accelerated life testing are analyzed to illustrate the practical usefulness of the proposed methods.
Document
Document information
Published on 21/09/26
Accepted on 30/03/26
Submitted on 19/01/26
Volume 42, Issue 6, 2026
DOI: 10.23967/j.rimni.2026.10.79283
Licence: CC BY-NC-SA license
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