关于哈尔滨工业大学张阳春博士学术报告会的通知

报告题目：A supplement on CLT for LSS under a large dimensional generalized spiked covariance model
报  告  人：张阳春  博士(哈尔滨工业大学)
报告时间：2019年9月30日（星期一）下午 16:00-17:00                
报告地点：4号楼318室
邀  请  人：王绍臣  博士
        欢迎广大师生前往！

数学学院

2019年9月29日

报告摘要：

Central limit theorem (CLT) for linear spectral statistics (LSSs) is widely used in large scale statistical inference when the sample size n and dimension p both tend to infinity. However, there always exists discrepancy between the sample mean and sample variance, and asymptotic mean and asymptotic variance when the CLT is applied for an LSS under spiked models. A major portion of the discrepancy is from the spiked eigenvalues, which depends on the dimensions (p; n) and the magnitudes of the spikes. In order to eliminate such discrepancy, we propose in this paper a supplement to the CLT defined as Hp CLT for a class of LSSs of sample covariance matrices. Simulation results demonstrate the success of the Hp CLT and exhibit its superiority to the original ones in various situations.