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  • 标题:Asymptotic Expansion Under Degeneracy
  • 本地全文:下载
  • 作者:Yuji Sakamoto ; Nakahiro Yoshida
  • 期刊名称:JOURNAL OF THE JAPAN STATISTICAL SOCIETY
  • 印刷版ISSN:1882-2754
  • 电子版ISSN:1348-6365
  • 出版年度:2003
  • 卷号:33
  • 期号:2
  • 页码:145-156
  • DOI:10.14490/jjss.33.145
  • 出版社:JAPAN STATISTICAL SOCIETY
  • 摘要:We will consider a stochastic expansion described by random variables whose covariance matrix is asymptotically degenerate. Though the conventional approach with Bhattacharya-Ghosh's transform requires the nondegeneracy of the covariance matrix, it is known that this method still works even in degenerate cases with the help of the so-called global approach. In this paper, we explain this fact and also mention, as an example, the third order asymptotic expansion of the maximum likelihood estimator for the O-U process.
  • 关键词:asymptotic expansion;diffusion functional;M-estimator;mixing process
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