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  • 标题:APPROXIMATION FOR DENSITY OF ESTIMATORS IN GAUSSIAN AR (1) PROCESS
  • 本地全文:下载
  • 作者:Yoshihide Kakizawa
  • 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:2
  • 页码:161-172
  • DOI:10.14490/jjss1995.26.161
  • 出版社:JAPAN STATISTICAL SOCIETY
  • 摘要:This paper deals with the density for a class of estimators _??_ c 1 c 2 ( c 1, c 2≥0) in Gaussian AR (1) process. Here _??_ c 1 c 2 includes various estimators if the constants c 1 and c 2 are specified appropriately. Applying the saddlepoint method to the general formula by Geary [5], the density of _??_ c 1 c 2 is approximated. Although Phillips [14] pointed out that the saddlepoint density is undefined in a substantial part of the tails, we elucidate that the resulting approximation is always defined if c 1 and c 2 are appropriately chosen. Some numerical comparisons are made among the Edgeworth approximation, the saddlepoint approximation, and the exact distribution for _??_1/2, 1/2. We also approximate the density for the mean corrected estmator _??_ c 1 c 2.
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