Accelerated test system strength models based on Birnbaum–Saunders distribution: a complete Bayesian analysis and comparison

被引:0
|
作者
S. K. Upadhyay
Bhaswati Mukherjee
Ashutosh Gupta
机构
[1] Banaras Hindu University,Department of Statistics and DST Centre for Interdisciplinary Mathematical Sciences
[2] Bristol Myers Squibb India Pvt. Ltd.,Department of Global Biometric Sciences
[3] GlaxoSmithKline Pharmaceuticals Limited,Biomedical Data Sciences India
来源
Lifetime Data Analysis | 2009年 / 15卷
关键词
Birnbaum–Saunders distribution; Cumulative damage model; Size effect; Gibbs sampler; Metropolis algorithm; Hybrid strategy; Predictive simulation; Partial posterior predictive ; -value; Bayesian information criterion; Deviance information criterion; Posterior predictive loss;
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摘要
Several models for studies related to tensile strength of materials are proposed in the literature where the size or length component has been taken to be an important factor for studying the specimens’ failure behaviour. An important model, developed on the basis of cumulative damage approach, is the three-parameter extension of the Birnbaum–Saunders fatigue model that incorporates size of the specimen as an additional variable. This model is a strong competitor of the commonly used Weibull model and stands better than the traditional models, which do not incorporate the size effect. The paper considers two such cumulative damage models, checks their compatibility with a real dataset, compares them with some of the recent toolkits, and finally recommends a model, which appears an appropriate one. Throughout the study is Bayesian based on Markov chain Monte Carlo simulation.
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页码:379 / 396
页数:17
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