Combined Variance Reduction and Output Analysis in Stochastic Simulation

拟议的研究旨在开发新的方法， 同时应用方差缩减技术， 估计和输出分析方法，对于有效的区间估计， 在随机模拟实验中。 将执行三项任务： 综合方差减少技术和产出的检查 稳态仿真实验分析方法的扩展 现有的方差减少技术的多变量参数 估计在终止模拟，和发展的一个 选择和参数化方差缩减技术的框架 在顺序执行的实验中，例如通过 仿真成功完成这些任务将导致更广泛的 应用有效的方差缩减和适当的输出 分析.

The proposed research seeks to develop new methods for simultaneously applying variance reduction techniques, for precise point estimation, and output analysis methods, for valid interval estimation, in stochastic simulation experiments. Three tasks will be performed: examination of combined variance reduction techniques and output analysis methods for steady-state simulation experiments, the extension of existing variance reduction techniques to multivariate parameter estimation in terminating simulations, and the development of a framework for selecting and parameterizing variance reduction techniques in experiments performed sequentially, such as optimization via simulation. Successful completion of these tasks will lead to wider application of effective variance reduction and appropriate output analysis.