Neparametrická diskriminační analýza

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Title in English Nonparametric discriminant analysis
Authors

FORBELSKÁ Marie

Year of publication 2001
Type Article in Proceedings
Conference Sborník prací 11. letní školy ROBUST 2000
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 This article compares the performance of parametric and nonparametric discrimination. The multivariate product polynomial kernels with data-driven choices of the bandwidth are used for density estimators and this nonparametric approach are compared with classical one by some simulated data.
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