Fisher Information inequalities and the Central Limit Theorem
Statistics Theory
2007-06-13 v2 Probability
Statistics Theory
Abstract
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.
Cite
@article{arxiv.math/0111020,
title = {Fisher Information inequalities and the Central Limit Theorem},
author = {Oliver Johnson and Andrew Barron},
journal= {arXiv preprint arXiv:math/0111020},
year = {2007}
}
Comments
19 pages