Proceedings of the Korean Statistical Society Conference (한국통계학회:학술대회논문집)
- 2002.05a
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- Pages.1-5
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- 2002
Optimal bandwidth in nonparametric classification between two univariate densities
- Hall, Peter (Centre for Mathematics and its Applications, Australian National University) ;
- Kang, Kee-Hoon (Department of Statistics, Hankuk University of Foreign Studies)
- ;
- 강기훈
- Published : 2002.05.24
Abstract
We consider the problem of optimal bandwidth choice for nonparametric classification, based on kernel density estimators, where the problem of interest is distinguishing between two univariate distributions. When the densities intersect at a single point, optimal bandwidth choice depends on curvatures of the densities at that point. The problem of empirical bandwidth selection and classifying data in the tails of a distribution are also addressed.
Keywords
- Bandwidth selection;
- Bayes risk;
- bootstrap;
- cross-validation;
- discrimination;
- classification error;
- error rate;
- kernel methods;
- nonparametric density estimation