The Generalized Cross Entropy Method, with Applications to Probability Density Estimation |
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Authors: | Zdravko I. Botev Dirk P. Kroese |
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Affiliation: | 1. Department of Mathematics, The University of Queensland, Brisbane, 4072, Australia
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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. |
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