On Reliability in a Multicomponent Stress-Strength Model with Power Lindley Distribution

Q3 Mathematics

Revista Colombiana De Estadistica Pub Date : 2018-07-01 DOI:10.15446/RCE.V41N2.69621

Abbas Pak, Arjun K. Gupta, N. B. Khoolenjani

引用次数: 17

Abstract

In this paper we study the reliability of a multicomponent stress-strength model assuming that the components follow power Lindley model. The maximum likelihood estimate of the reliability parameter and its asymptotic confidence interval are obtained. Applying the parametric Bootstrap technique, interval estimation of the reliability is presented. Also, the Bayes estimate and highest posterior density credible interval of the reliability parameter are derived using suitable priors on the parameters. Because there is no closed form for the Bayes estimate, we use the Markov Chain Monte Carlo method to obtain approximate Bayes estimate of the reliability. To evaluate the performances of different procedures, simulation studies are conducted and an example of real data sets is provided.

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具有幂Lindley分布的多组分应力强度模型的可靠性

在本文中，我们研究了假设构件遵循幂Lindley模型的多组分应力强度模型的可靠性。得到了可靠性参数的最大似然估计及其渐近置信区间。应用参数自举技术，给出了可靠性的区间估计。此外，利用参数的适当先验，导出了可靠性参数的贝叶斯估计和最高后验密度可信区间。由于贝叶斯估计不存在闭合形式，我们使用马尔可夫链蒙特卡罗方法来获得可靠性的近似贝叶斯估计。为了评估不同程序的性能，进行了仿真研究，并提供了一个真实数据集的例子。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Revista Colombiana De Estadistica STATISTICS & PROBABILITY-

CiteScore

1.20

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The Colombian Journal of Statistics publishes original articles of theoretical, methodological and educational kind in any branch of Statistics. Purely theoretical papers should include illustration of the techniques presented with real data or at least simulation experiments in order to verify the usefulness of the contents presented. Informative articles of high quality methodologies or statistical techniques applied in different fields of knowledge are also considered. Only articles in English language are considered for publication. The Editorial Committee assumes that the works submitted for evaluation have not been previously published and are not being given simultaneously for publication elsewhere, and will not be without prior consent of the Committee, unless, as a result of the assessment, decides not publish in the journal. It is further assumed that when the authors deliver a document for publication in the Colombian Journal of Statistics, they know the above conditions and agree with them.