Confidence limits to the distance of the true distribution from a misspecified family by bootstrap

被引:2
作者
Babu, GJ [1 ]
Rao, CR [1 ]
机构
[1] Penn State Univ, Dept Stat, University Pk, PA 16802 USA
关键词
Brownian motion; empirical process; bootstrap; L-statistics; median; Kolmogorov-Smimov statistic; Cramer-von Mises statistic; Kullback-Leibler measure;
D O I
10.1016/S0378-3758(02)00176-3
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
In statistical practice, an estimated distribution function (d.f.) from a specified family is used for taking decisions. When the true d.f. from which samples are drawn does not belong to the specified family, it is of interest to know how close the true d.f. is to the specified family. In this paper, we use non-parametric bootstrap to obtain confidence limits to the difference between the true d.f. and a member of the specified family closest to it in the sense of Kullback-Leibler measure. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:471 / 478
页数:8
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