| Título: | A Weak Law of Large Numbers for the Sample Covariance Matrix |
| Autores: |
Sepanski, Steven J.; Saginaw Valley State University Pan, Zhidong; Saginaw Valley State University |
| Fecha: | 2000-01-01 |
| Publicador: | Electronic communications in probability |
| Fuente: |
 |
| Tipo: |
Peer-reviewed Article |
| Tema: | Law of large numbers, affine normalization, samplecovariance, central limit theorem, domain of attraction, generalized domain of attraction, multivariate t statistic |
| Descripción: | In this article we consider the sample covariance matrix formed from a sequence of independent and identically distributed random vectors from the generalized domain of attraction of the multivariate normal law. We show that this sample covariance matrix, appropriately normalized by a nonrandom sequence of linear operators, converges in probability to the identity matrix. |
| Idioma: | No aplica |
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