Name
Abstract | ||
|---|---|---|
In this article, we propose tests for covariance matrices of high dimension with fewer observations than the dimension for a general class of distributions with positive definite covariance matrices. In the one-sample case, tests are proposed for sphericity and for testing the hypothesis that the covariance matrix @S is an identity matrix, by providing an unbiased estimator of tr[@S^2] under the general model which requires no more computing time than the one available in the literature for a normal model. In the two-sample case, tests for the equality of two covariance matrices are given. The asymptotic distributions of proposed tests in the one-sample case are derived under the assumption that the sample size N=O(p^@d),1/2 |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.jmva.2014.06.003 | J. Multivariate Analysis |
Keywords | Field | DocType |
sample size smaller than dimension,high dimension,non-normal model,secondary,test statistics,asymptotic distributions,primary,covariance matrix | Econometrics,Covariance function,Combinatorics,Estimation of covariance matrices,Rational quadratic covariance function,Matrix (mathematics),Law of total covariance,Multivariate random variable,Covariance matrix,Statistics,Mathematics,Covariance | Journal |
Volume | ISSN | Citations |
130, | 0047-259X | 8 |
PageRank | References | Authors |
1.10 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muni S. Srivastava | 1 | 76 | 17.08 |
| Hirokazu Yanagihara | 2 | 21 | 8.66 |
| Tatsuya Kubokawa | 3 | 36 | 11.73 |