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  • 统计与管理学院2017年学术报告第2

     

    【主  题】Efficient Monte Carlo evaluation of resampling-based hypothesis tests

    【报告人】 Wing Kam Fung, Ph.D.

    The University of Hong Kong

    【时  间】 2017年03月08日(星期三)15:00-16:00

    【地  点】 上海财经大学统计与管理学院大楼1208室

    【摘  要】Monte Carlo evaluation of resampling-based tests is often conducted in statistical analysis. However, this procedure is generally computationally intensive. The pooling resampling-based method has been developed to reduce the computational burden but the validity of the method has not been studied before. In this talk, we first investigate the asymptotic properties of the pooling resampling-based method, and then propose a novel Monte Carlo evaluation procedure namely the n-times pooling resampling-based method. Theorems as well as simulations show that the proposed method can give smaller or comparable root mean squared errors and bias with much less computing time, thus can be strongly recommended especially for evaluating highly computationally intensive hypothesis testing procedures in genetic epidemiology.

    【邀请人】 柏杨