專題演講 主講人:王紹宣教授(中央大學統計所)

  • 2020-11-20
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題 目:On asymptotic normality of CDM-PCA in HDLSS

主講人:王紹宣教授(中央大學統計所)
        
時 間:109年11月20日(星期五)上午10:40-11:30

(上午10:20-10:40茶會於交大統計所428室舉行) 

地 點:交大綜合一館427室

 
摘要
 
Principal component analysis in high dimension low sample size setting has been an active research area in recent years. Yata and Aoshima (2010) proposed a cross data matrix-based method and showed the asymptotic normality for estimates of spiked eigenvalues and also consistency for corresponding estimates of PC directions. However, the asymptotic normality for estimates of PC directions is still lacking. In this work, we have extended Yata and Aoshima's work to include the investigation of the asymptotic normality for the leading CDM-based PC directions and to compare it with the asymptotic normality for the classical PCA. Numerical examples are provided to illustrate the asymptotic normality.
 


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