A weighted bootstrap approximation of the maximal deviation of kernel density estimates over general compact sets
A weighted bootstrap approximation of the maximal deviation of kernel density estimates over general compact sets
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一般紧集上核密度估计最大偏差的加权引导近似
DOI：
10.1016/j.jmva.2012.06.008
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
M. Mojirsheibani
中科院分区：
文献类型：
--
作者：
M. Mojirsheibani
本文考虑一种加权Bootstrap方法来逼近一般连通紧集上核密度估计的最大偏差Bootstrap-MBR.tex的分布。同时也证明了该近似的理论正确性。此外，仿真研究表明，与大样本理论以及Efron(1979)的原始Bootstrap相比，所提出的加权Bootstrap具有更好的有限样本性能，这取决于权重的选择。
This article considers a weighted bootstrap method to approximate the distribution of the maximal deviatiBootstrap-MBR.texon of kernel density estimates over general connected compact sets. The theoretical validity of this approximation is also established. Furthermore, simulation studies show that, depending on the choice of the weights, the proposed weighted bootstrap can have a superior finite-sample performance as compared to both the large-sample theory as well as Efron’s (1979) original bootstrap.