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  • 标题:JACKKNIFING: HIGHER ORDER ACCURATE CONFIDENCE INTERVALS
  • 本地全文:下载
  • 作者:Jin Fang Wang ; Masaaki Taguri
  • 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:1996
  • 卷号:26
  • 期号:1
  • 页码:69-82
  • DOI:10.14490/jjss1995.26.69
  • 出版社:JAPAN STATISTICAL SOCIETY
  • 摘要:Higher order asymptotic aspects of the jackknife- t method are studied. Emphasis is placed upon constructing higher order accurate confidence intervals for parameters which are smooth functions of multivariate means. Explicit formulae for two-term Edgeworth corrections for both cumulative distribution functions and percentiles are provided. These formulae can be automatically evaluated given specific distributions. Jackknife- t confidence intervals having coverage error of O ( n -3/2), n being the sample size, are obtained by twice inverting certain Edgeworth expansion. A numerical example is given in the case of estimating the coefficient of variation from normal populations. Bootstrap intervals are also discussed.
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