Assessing the quality of bootstrap samples and of the bootstrap estimates obtained with finite resampling

被引:23
|
作者
Yatracos, Y [1 ]
机构
[1] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117543, Singapore
关键词
bootstrap estimate; bootstrap geometry; bootstrap sample; inadmissibility; jackknife; model dimension;
D O I
10.1016/S0167-7152(02)00196-7
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
It is seen in simulations and confirmed theoretically that: (i) the loss in accuracy of the Monte Carlo approximation of the bootstrap estimate can be infinite, due to the additional uncertainty introduced by finite resampling, and (ii) the dimension of the data or the estimate of interest affect drastically the quality of the bootstrap samples and estimates. Based on the findings, directions are provided to improve the bootstrap methodology. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
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页码:281 / 292
页数:12
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