Two multivariate central limit theorems

dc.creatorMeckes, Elizabeth
dc.date2007-06-06
dc.date.accessioned2026-07-07T08:04:21Z
dc.date.available2026-07-07T08:04:21Z
dc.descriptionIn this paper, explicit error bounds are derived in the approximation of rank $k$ projections of certain $n$-dimensional random vectors by standard $k$-dimensional Gaussian random vectors. The bounds are given in terms of $k$, $n$, and a basis of the $k$-dimensional space onto which we project. The random vectors considered are two generalizations of the case of a vector with independent, identically distributed components. In the first case, the random vector has components which are independent but need not have the same distribution. The second case deals with finite exchangeable sequences of random variables.
dc.description10 pages
dc.identifierhttps://arxiv.org/abs/0706.0844
dc.identifierhttp://arxiv.org/abs/0706.0844
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/129928
dc.subjectProbability
dc.titleTwo multivariate central limit theorems
dc.typetext

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