Neparametrická diskriminační analýza

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Title in English Nonparametric discrimination analysis
Authors

FORBELSKÁ Marie

Year of publication 2000
Type Article in Proceedings
Conference Biometrické metody a modely v podohospodárskej vede, výskume a výuke
MU Faculty or unit

Faculty of Science

Citation
Field Applied statistics, operation research
Keywords Linear and quadratic discrimination analysis; nonparametric discrimination analysis; kernel estimators of density function; product kernels.
Description Attention is focused here on the application of kernel density estimation to statistical discrimination. In order to place the nonparametric approach in context, the classical approach to discriminant analysis is reviewed very briefly. Kernel smoothers are one of the most popular nonparametric functional estimates and there are used multivariate product polynomial kernels and data-driven choices for the bandwidth. The theoretical considerations are illustrated with some examples.
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