DocumentCode
1367171
Title
About the asymptotic accuracy of Barron density estimates
Author
Berlinet, Alain ; Vajda, Igor ; Van der Meulen, Edward C.
Author_Institution
Dept. of Stat., Univ. des Sci. et Tech. du Languedoc, Montpellier, France
Volume
44
Issue
3
fYear
1998
fDate
5/1/1998 12:00:00 AM
Firstpage
999
Lastpage
1009
Abstract
By extending the information-theoretic arguments of previous papers dealing with the Barron-type density estimates, and their consistency in information divergence and chi-square divergence, the problem of consistency in Csiszar´s φ-divergence is motivated for general convex functions φ. The problem of consistency in φ-divergence is solved for all φ with φ(0)<∞ and φ(t)=O(t ln t) when t→∞. The problem of consistency in the expected φ-divergence is solved for all φ with tφ(1/t)+φ(t)=O(t2) when t→∞. Various stronger versions of these asymptotic restrictions are considered too. Assumptions about the model needed for the consistency are shown to depend on how strong these restrictions are
Keywords
estimation theory; information theory; nonparametric statistics; Barron density estimates; Csiszar´s φ-divergence; Renyi distances; asymptotic accuracy; chi-square divergence; general convex functions; information divergence; information-theoretic arguments; nonparametric density estimates; Automation; Histograms; Information theory; Kernel; Mathematics; Packaging; Statistics; Topology;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.669143
Filename
669143
Link To Document