Estimation of misclassification probabilities by bootstrap methods
作者:
Samprit Chatterjee,
Sangit Chatterjee,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1983)
卷期:
Volume 12,
issue 6
页码: 645-656
ISSN:0361-0918
年代: 1983
DOI:10.1080/03610918308812350
出版商: Marcel Dekker, Inc.
关键词: bootstrap;discriminant functions;error rates;jackknife
数据来源: Taylor
摘要:
Several methods have been proposed to estimate the misclassification probabilities when a linear discriminant function is used to classify an observation into one of several populations. We describe the application of bootstrap sampling to the above problem. The proposed method has the advantage of not only furnishing the estimates of misclassification probabilities but also provides an estimate of the standard error of estimate. The method is illustrated by a small simulation experiment. It is then applied to three published, well accessible data sets, which are typical of large, medium and small data sets encountered in practice.
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