典型文献
A Test on High-Dimensional Intraclass Correlation Structure
文献摘要：
The paper considers a high-dimensional likelihood ratio(LR)test on the intraclass correlation structure of the multivariate normal population.When the di-mension p and sample size N satisfy N-1＞p→∞,it is proved that the logarithmic LR statistic asymptotically obeys Gaussian distribution,and the explicit expressions of the mean and the variance are also obtained.The simulations demonstrate that our high-dimensional LR test method outperforms the traditional Chi-square approxi-mation method or F-approximation method,and performs as efficient as the accurate high-dimensional Edgeworth expansion method and the more accurate high-dimensional Edgeworth expansion method in analyzing the intraclass covariance structure of high-dimensional data.
文献关键词：
中图分类号：
作者姓名：
TANG Ping;XIAO Nan-nan;XIE Jun-shan
作者机构：
School of Mathematics and Statistics,Henan University,Kaifeng 475004,China
文献出处：
引用格式：
[1]TANG Ping;XIAO Nan-nan;XIE Jun-shan-.A Test on High-Dimensional Intraclass Correlation Structure)[J].数学季刊（英文版）,2022(01):10-25
A类：
Intraclass,Edgeworth
B类：
Test,High,Dimensional,Correlation,Structure,paper,considers,high,dimensional,likelihood,ratio,LR,test,intraclass,correlation,structure,multivariate,normal,population,When,sample,size,satisfy,proved,that,logarithmic,statistic,asymptotically,obeys,Gaussian,distribution,explicit,expressions,mean,also,obtained,simulations,demonstrate,our,method,outperforms,traditional,Chi,square,approximation,efficient,accurate,expansion,more,analyzing,covariance,data
AB值：
0.529731
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