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A0217
Title: On asymptotic normality of CDM-PCA in HDLSS Authors:  Su-Yun Huang - Academia Sinica (Taiwan)
Ting-Li Chen - Academia Sinica (Taiwan)
Shao-Hsuan Wang - National Central University (Taiwan) [presenting]
Abstract: Principal component analysis in high dimension low sample size setting has been an active research area in recent years. A cross data matrix-based method showed the asymptotic normality for estimates of spiked eigenvalues, and also consistency for corresponding estimates of PC directions was previously proposed. However, the asymptotic normality for estimates of PC directions is still lacking. We have extended previous 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.