A simple resampling method by perturbing the minimand

被引:223
作者
Jin, ZZ
Ying, ZL
Wei, LJ
机构
[1] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
[2] Columbia Univ, Dept Stat, New York, NY 10027 USA
基金
美国国家卫生研究院;
关键词
bootstrap; heteroscedastic regression; L-p norm; resampling method; truncated regression; U-process;
D O I
10.1093/biomet/88.2.381
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Suppose that under a semiparametric setting an estimator of a vector of parameters of interest is obtained by optimising an objective function which has a U-process structure. The covariance matrix of the estimator is generally a function of the underlying density function, which may be difficult to estimate well by conventional methods. In this paper, we present a simple resampling method by perturbing the objective function repeatedly. Inferences of the parameters can then be made based on a large collection of the resulting optimisers. We illustrate our proposal by three examples with a heteroscedastic regression model.
引用
收藏
页码:381 / 390
页数:10
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