Fisher Information inequalities and the Central Limit Theorem

Simple item page
dc.creatorJohnson, Oliver
dc.creatorBarron, Andrew
dc.date2001-11-02
dc.date2003-07-04
dc.date.accessioned2026-07-07T08:05:59Z
dc.date.available2026-07-07T08:05:59Z
dc.descriptionWe give conditions for an O(1/n) rate of convergence of Fisher information and relative entropy in the Central Limit Theorem. We use the theory of projections in L2 spaces and Poincare inequalities, to provide a better understanding of the decrease in Fisher information implied by results of Barron and Brown. We show that if the standardized Fisher information ever becomes finite then it converges to zero.
dc.description19 pages
dc.identifierhttps://arxiv.org/abs/math/0111020
dc.identifierhttp://arxiv.org/abs/math/0111020
dc.identifierProbability Theory and Related Fields, Vol 129/3, 2004, pages 391-409
dc.identifierdoi:10.1007/s00440-004-0344-0
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130457
dc.subjectStatistics Theory
dc.subjectProbability
dc.subject62B10, 60F05, 94A17
dc.titleFisher Information inequalities and the Central Limit Theorem
dc.typetext

Files

Collections

arXiv