The generalized cross entropy method, with applications to probability density estimation

Botev, Zdravko I. and Kroese, Dirk P. (2011) The generalized cross entropy method, with applications to probability density estimation. Methodology and Computing in Applied Probability, 13 1: 1-27. doi:10.1007/s11009-009-9133-7

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Author Botev, Zdravko I.
Kroese, Dirk P.
Title The generalized cross entropy method, with applications to probability density estimation
Journal name Methodology and Computing in Applied Probability   Check publisher's open access policy
ISSN 1387-5841
Publication date 2011-02
Year available 2009
Sub-type Article (original research)
DOI 10.1007/s11009-009-9133-7
Open Access Status File (Author Post-print)
Volume 13
Issue 1
Start page 1
End page 27
Total pages 27
Editor Joseph Glaz
Place of publication United States
Publisher Springer
Collection year 2010
Language eng
Subject 970101 Expanding Knowledge in the Mathematical Sciences
970108 Expanding Knowledge in the Information and Computing Sciences
010405 Statistical Theory
010303 Optimisation
010205 Financial Mathematics
010206 Operations Research
Abstract Nonparametric density estimation aims to determine the sparsest model that explains a given set of empirical data and which uses as few assumptions as possible. Many of the currently existing methods do not provide a sparse solution to the problem and rely on asymptotic approximations. In this paper we describe a framework for density estimation which uses information-theoretic measures of model complexity with the aim of constructing a sparse density estimator that does not rely on large sample approximations. The effectiveness of the approach is demonstrated through an application to some well-known density estimation test cases.
Keyword Cross entropy
Information theory
Monte Carlo simulation
Statistical modeling
Kernel smoothing
Functional optimization
Bandwidth selection
Calculus of variations
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
2010 Higher Education Research Data Collection
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Citation counts: TR Web of Science Citation Count  Cited 5 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 11 times in Scopus Article | Citations
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Created: Wed, 24 Mar 2010, 16:05:20 EST by Kay Mackie on behalf of School of Mathematics & Physics