步进应力部分加速寿命试验模型下林德利分布广义渐进混合截尾数据的统计分析

IF 0.6 Q4 STATISTICS & PROBABILITY
Aakriti Pandey, A. Kaushik, S. Singh, U. Singh
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引用次数: 6

摘要

本文的目的是给出在广义渐进混合滤波方案下阶跃应力部分加速寿命试验模型的估计方法。假设不确定性服从林德利分布。研究了步进应力部分加速寿命试验模型中参数的点估计和区间估计以及加速因子的极大似然估计问题。通过仿真研究,利用均方误差对所考虑的滤波方案下估计器的性能进行了监测。计算加速条件下试验的预期总时间,以检验参数对试验持续时间的影响。此外,还提供了加速和非加速条件下测试的预期总时间图,以突出显示由于加速而产生的影响。为了说明问题,我们分析了一个真实的数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Analysis for Generalized Progressive Hybrid Censored Data from Lindley Distribution under Step-Stress Partially Accelerated Life Test Model
The aim of this paper is to present the estimation procedure for the step-stress partially accelerated life test model under the generalized progressive hybrid censoring scheme. The uncertainties are assumed to be governed by Lindley distribution. The problem with point and interval estimation of the parameters as well as the acceleration factor using maximum likelihood approach for the step-stress partially accelerated life test model has been considered. A simulation study is conducted to monitor the performance of the estimators on the basis of the mean squared error under the considered censoring scheme. The expected total time of the test under an accelerated condition is computed to examine the effects of the parameters on the duration of the test. In addition, a graph of the expected total time of the test under accelerated and un-accelerated conditions is provided to highlight the effect due to acceleration. One real data set has been analyzed for illustrative purposes.
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来源期刊
Austrian Journal of Statistics
Austrian Journal of Statistics STATISTICS & PROBABILITY-
CiteScore
1.10
自引率
0.00%
发文量
30
审稿时长
24 weeks
期刊介绍: The Austrian Journal of Statistics is an open-access journal (without any fees) with a long history and is published approximately quarterly by the Austrian Statistical Society. Its general objective is to promote and extend the use of statistical methods in all kind of theoretical and applied disciplines. The Austrian Journal of Statistics is indexed in many data bases, such as Scopus (by Elsevier), Web of Science - ESCI by Clarivate Analytics (formely Thompson & Reuters), DOAJ, Scimago, and many more. The current estimated impact factor (via Publish or Perish) is 0.775, see HERE, or even more indices HERE. Austrian Journal of Statistics ISNN number is 1026597X Original papers and review articles in English will be published in the Austrian Journal of Statistics if judged consistently with these general aims. All papers will be refereed. Special topics sections will appear from time to time. Each section will have as a theme a specialized area of statistical application, theory, or methodology. Technical notes or problems for considerations under Shorter Communications are also invited. A special section is reserved for book reviews.
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