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文章基本信息

  • 标题:Approximating distribution functions by iterated function systems
  • 本地全文:下载
  • 作者:Stefano Maria Iacus ; Davide La Torre
  • 期刊名称:Advances in Decision Sciences
  • 印刷版ISSN:2090-3359
  • 电子版ISSN:2090-3367
  • 出版年度:2005
  • 卷号:2005
  • 期号:1
  • 页码:33-46
  • DOI:10.1155/JAMDS.2005.33
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    An iterated function system (IFS) on the space of distribution functions is built with the aim of proposing a new class of distribution function estimators. One IFS estimator and its asymptotic properties are studied in detail. We also propose a density estimator derived from the IFS distribution function estimator by using Fourier analysis. Relative efficiencies of both estimators, for small and moderate sample sizes, are presented via Monte Carlo analysis.

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