arXiv:math/0111020 [math.ST]AbstractReferencesReviewsResources
Fisher Information inequalities and the Central Limit Theorem
Published 2001-11-02, updated 2003-07-04Version 2
We 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.
Comments: 19 pages
Journal: Probability Theory and Related Fields, Vol 129/3, 2004, pages 391-409
Keywords: central limit theorem, fisher information inequalities, l2 spaces, poincare inequalities, standardized fisher information
Tags: journal article
Related articles: Most relevant | Search more
arXiv:1911.01985 [math.ST] (Published 2019-11-05)
Behavior of Fréchet mean and Central Limit Theorems on spheres
arXiv:1605.07056 [math.ST] (Published 2016-05-23)
A note on central limit theorems for quadratic variation in case of endogenous observation times
arXiv:1008.3954 [math.ST] (Published 2010-08-24)
Central limit theorem of nonparametric estimate of spectral density functions of sample covariance matrices