Divergence-type errors of smooth Barron-type density estimators

• Autores: Jan Beirlant, Igor Vajda, Gérard Biau , Alain Berlinet
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 11, Nº. 1, 2002, págs. 191-217
• Idioma: inglés
• DOI: 10.1007/bf02595736
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• Resumen

  • Barron-type estimators are histogram-based distribution estimators that have been proved to have good consistency properties according to several information theoretic criteria. However they are not continuous. In this paper, we examine a new class of continuous distribution estimators obtained as a combination of Barron-type estimators with the frequency polygon. We prove the consistency of these estimators in expected information divergence and expected ?2-divergence. For one of them we evaluate the rate of convergence in expected ?2-divergence