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Validation and statistical analysis procedures under the common random number correlation-induction strategy for multipopulation simulation experiments

机译:通用随机数相关归纳策略下多种群模拟实验的验证和统计分析程序

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摘要

This paper provides a validation procedure and statistical analysis methods for multipopulation simulation experiments conducted under the common random number correlation-induction strategy in order to fit a metamodel of interest between the mean response and a selected set of input factors. Before conducting the statistical analysis, we need to validate certain key assumptions made for the CRN strategy, which, if violated, render the proposed statistical analysis invalid. Validation is composed of a three-step statistical procedure. The first step tests for multivariate normality, the second step tests the structure of the covariance matrix between responses, and the third step tests for the adequacy of the proposed metamodel. The proposed statistical analysis provides optimal (UMVU) estimates for the unknown metamodel parameters and gives optimal simultaneous confidence intervals on linear combinations of these parameters. Both the validation procedure and statistical analysis methods are illustrated with an example of a hospital simulation study.
机译:本文提供了一种验证程序和统计分析方法,用于在通用随机数相关性诱导策略下进行的多种群模拟实验,以便在均值响应和一组选定的输入因子之间拟合感兴趣的元模型。在进行统计分析之前,我们需要验证针对CRN策略所做的某些关键假设,如果违反这些假设,则会使建议的统计分析无效。验证由三步统计程序组成。第一步测试多元正态性,第二步测试响应之间的协方差矩阵的结构,第三步测试拟议元模型的适当性。拟议的统计分析为未知的元模型参数提供了最佳(UMVU)估计,并为这些参数的线性组合提供了最佳的同时置信区间。以医院模拟研究为例说明了验证程序和统计分析方法。

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