Conditional confidence intervals for classification error rate

被引：7
|
作者：
Chung, Hie-Choon [1 ]
Han, Chien-Pai [2 ]
机构：
[1] Gwangju Univ, Dept E Business, Kwangju 503703, South Korea
[2] Univ Texas Arlington, Dept Math, Arlington, TX 76019 USA
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2009年 / 53卷 / 12期
关键词：
DISCRIMINANT-ANALYSIS; CROSS-VALIDATION; BOOTSTRAP METHODS; MISCLASSIFICATION; PROBABILITY; JACKKNIFE; RULE;
D O I：
10.1016/j.csda.2009.06.009
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
An observation is to be classified into one of several multivariate normal populations with equal covariance matrix. When the parameters are unknown, independent training samples are taken from the populations. We consider the construction of confidence intervals for the conditional error rate. The cases of two populations and three populations are studied in detail. We propose the conditional jackknife confidence interval and the conditional bootstrap confidence intervals of the conditional error rate. A Monte Carlo study is conducted to compare the confidence intervals. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码：4358 / 4369
页数：12
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