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文章基本信息

  • 标题:Divergence measures estimation and its asymptotic normality theory using wavelets empirical processes II
  • 作者:Amadou Dadié Ba ; Gane Samb Lo ; Diam Ba
  • 期刊名称:Afrika Statistika
  • 印刷版ISSN:0825-0305
  • 出版年度:2018
  • 卷号:13
  • 期号:2
  • 页码:1667-1681
  • 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.

  • 关键词:Divergence measures estimation; Asymptotic normality; Wavelet theory; wavelets empirical processes; Besov spaces
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