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High Dimensional Probability VIIStability of Cramer’s Characterization of Normal Laws in Information Distances

High Dimensional Probability VII: Stability of Cramer’s Characterization of Normal Laws in... [Optimal stability estimates in the class of regularized distributions are derived for the characterization of normal laws in Cramer’s theorem with respect to relative entropy and Fisher information distance.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

High Dimensional Probability VIIStability of Cramer’s Characterization of Normal Laws in Information Distances

Part of the Progress in Probability Book Series (volume 71)
Editors: Houdré, Christian; Mason, David M.; Reynaud-Bouret, Patricia; Rosiński, Jan

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References (18)

Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2016
ISBN
978-3-319-40517-9
Pages
3 –35
DOI
10.1007/978-3-319-40519-3_1
Publisher site
See Chapter on Publisher Site

Abstract

[Optimal stability estimates in the class of regularized distributions are derived for the characterization of normal laws in Cramer’s theorem with respect to relative entropy and Fisher information distance.]

Published: Sep 22, 2016

Keywords: Characterization of normal laws; Cramer’s theorem; Stability problems

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