Invariance principles for a multivariate Student process in the generalized domain of attraction of the multivariate normal law
Assuming that the sample correlation matrix of vector X converges to a positive definite nonstochastic matrix, we establish a uniform Euclidean norm approximation in probability and a functional CLT for a multivariate Student process, based on independent copies of X. These results obtain if and only if X is in the generalized domain of attraction of the multivariate normal law.
Year of publication: |
2012
|
---|---|
Authors: | Martsynyuk, Yuliya V. |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 82.2012, 12, p. 2270-2277
|
Publisher: |
Elsevier |
Subject: | Uniform Euclidean norm approximation in probability | Functional central limit theorem |
Saved in:
Saved in favorites
Similar items by subject
-
Csörgő, Miklós, (2011)
-
Račkauskas, Alfredas, (2020)
-
Semiparametric estimation of quantile treatment effects with endogeneity
Wüthrich, Kaspar, (2015)
- More ...
Similar items by person
-
Csörgő, Miklós, (2011)
-
Martsynyuk, Yuliya V., (2013)
- More ...