文章基本信息

标题：Divergence measures estimation and its asymptotic normality theory using wavelets empirical processes II
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作者：Amadou Dadié Ba ; Gane Samb Lo ; Diam Ba 等
期刊名称：Afrika Statistika
印刷版ISSN：2316-090X
出版年度：2018
卷号：13
期号：2
页码：1667-1681
语种：English
出版社：African journals online
摘要：In Ba et al.(2017), a general normal asymptotic theory for divergence measures estimators has been provided. These estimators are constructed from the wavelets empirical process and concerned the general Ø-divergence measures. In this paper, we first extend the aforementioned results to symmetrized forms of divergence measures. Second, the Tsallis and Renyi divergence measures as well as the Kullback-Leibler measures are investigated in details. The question of the applicability of the results, based on the boundedness assumption is also dealt, leading to future packages.