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  • 标题:Expansions for the Joint Distribution of the Sample Maximum and Sample Estimate
  • 本地全文:下载
  • 作者:Christopher S. Withers Industrial Research Limited ; NEW ZEALAND Saralees Nadarajah University of Manchester, UK
  • 期刊名称:Sankhya. Series A, mathematical statistics and probability
  • 印刷版ISSN:0976-836X
  • 电子版ISSN:0976-8378
  • 出版年度:2008
  • 卷号:70
  • 期号:01
  • 页码:109--123
  • 出版社:Indian Statistical Institute
  • 摘要:Let Fn be the empirical distribution of a random sample in Rp from a dis- tribution F. Let Mn be the componentwise sample maximum and T(F) a smooth functional in Rq. Let . = T(Fn). We use the conditional Edgeworth expansion for .|(Mn ≤ y) to obtain expansions for the joint distribution of (.,Mn). For T(F) = ¦Ì and ¦Ì2, their degree of dependence as measured by the strong¨Cmixing coefficient (.,Mn) is shown to be O(n.1/2) for a class of distributions associated with the EV3 (Weibull), O(n.1/2 logi n) for two classes associated with the EV1 (Gumbel) and O(ni/.1/2) for a class as- sociated with the EV2 () (Frechet), where i is the degree of T(F), that is i = 1 for ¦Ì and i = 2 for ¦Ì2,  = 1 for a class that includes the gamma, and  = 1/2 for a class that includes the normal.
  • 关键词:Edgeworth expansions, extreme value distributions, strong mixing coefficient.
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