A note on methods of restoring consistency to the bootstrap
A note on methods of restoring consistency to the bootstrap
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关于恢复引导程序一致性的方法的说明
DOI：
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发表时间：
2003
期刊：
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通讯作者：
R. Samworth
中科院分区：
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作者：
R. Samworth
我们考虑一致性的属性及其与确定引导程序性能的相关性。我们分析了 Hodges 和 Stein 估计器分布的各种参数自举近似，其行为是小波回归、核密度估计和非参数曲线拟合中使用的超高效估计器的典型行为。我们的结果不仅揭示了选择对直观引导程序进行良好修改的一些困难，而且即使在大样本中，不一致的引导程序近似也可能比一致的版本表现更好。版权所有 Biometrika Trust 2003，牛津大学出版社。
We consider the property of consistency and its relevance for determining the performance of the bootstrap. We analyse various parametric bootstrap approximations to the distributions of the Hodges and Stein estimators, whose behaviour is typical of that of super-efficient estimators employed in wavelet regression, kernel density estimation and nonparametric curve fitting. Our results reveal not only some of the difficulties in selecting good modifications to the intuitive bootstrap, but also that inconsistent bootstrap approximations may perform better than consistent versions even in large samples. Copyright Biometrika Trust 2003, Oxford University Press.