{"title":"Optimal sample size allocation for integrated test scheme","authors":"Guangling Dong, Chi He, Z. Dai","doi":"10.1109/CIVEMSA.2015.7158624","DOIUrl":null,"url":null,"abstract":"Integrated test scheme (ITS) make comprehensive use of simulation and field test to evaluate system performance, which takes on merits of low cost, full-scale assessment, and high precision. Sample size determination (SSD) methods for ITS are analyzed, which reveals the problem and contradiction in classical method and Bayesian method using standard power prior for design. Design effect of experiment is proposed considering the influence of prior sample size, which is used for elicitation of modified power prior for SSD of ITS. Taking average posterior variance for parameter of interest as the output precision, optimization equation for SSD of ITS under required posterior precision constraint is designed, whose effectiveness is illustrated with a utilization example.","PeriodicalId":348918,"journal":{"name":"2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIVEMSA.2015.7158624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

Integrated test scheme (ITS) make comprehensive use of simulation and field test to evaluate system performance, which takes on merits of low cost, full-scale assessment, and high precision. Sample size determination (SSD) methods for ITS are analyzed, which reveals the problem and contradiction in classical method and Bayesian method using standard power prior for design. Design effect of experiment is proposed considering the influence of prior sample size, which is used for elicitation of modified power prior for SSD of ITS. Taking average posterior variance for parameter of interest as the output precision, optimization equation for SSD of ITS under required posterior precision constraint is designed, whose effectiveness is illustrated with a utilization example.
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综合试验方案的最优样本量分配
综合测试方案综合运用仿真和现场测试对系统性能进行评估,具有成本低、全面评估、精度高等优点。分析了智能交通系统的样本量确定方法,揭示了采用标准功率先验设计的经典方法和贝叶斯方法存在的问题和矛盾。提出了考虑先验样本量影响的实验设计效果,用于ITS固态硬盘修正功率先验的推导。以感兴趣参数的平均后验方差作为输出精度,在要求的后验精度约束下,设计了ITS的SSD优化方程,并通过应用实例说明了其有效性。
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