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Description
| - The main approaches to discriminant analysis is considered with respect to the use of parametric models (based on the multivariate normal and elliptically contoured distributions), nonparametric models (based on the multivariate product Gaussian and polynomial kernels with various data-driven choices of the bandwidth) and also semiparametric models (based on the various kernel estimators for density functions of squared Mahalanobis distances). This paper demonstrates that linear and quadratic discriminant decision rules of classifying observation as coming from one of several multivariate normal distribution can be construct for much broader classes of distribution such as elliptical contoured distributions. While being much richer than the class of Gaussian distributions, the family of elliptically contoured distributions (ECD) inherits many of its attractive properties.
- The main approaches to discriminant analysis is considered with respect to the use of parametric models (based on the multivariate normal and elliptically contoured distributions), nonparametric models (based on the multivariate product Gaussian and polynomial kernels with various data-driven choices of the bandwidth) and also semiparametric models (based on the various kernel estimators for density functions of squared Mahalanobis distances). This paper demonstrates that linear and quadratic discriminant decision rules of classifying observation as coming from one of several multivariate normal distribution can be construct for much broader classes of distribution such as elliptical contoured distributions. While being much richer than the class of Gaussian distributions, the family of elliptically contoured distributions (ECD) inherits many of its attractive properties. (en)
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Title
| - A Comparison of Linear, Quadratic and Kernel Discriminant Rules for ECD Distributions Via ROC Analysis
- A Comparison of Linear, Quadratic and Kernel Discriminant Rules for ECD Distributions Via ROC Analysis (en)
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skos:prefLabel
| - A Comparison of Linear, Quadratic and Kernel Discriminant Rules for ECD Distributions Via ROC Analysis
- A Comparison of Linear, Quadratic and Kernel Discriminant Rules for ECD Distributions Via ROC Analysis (en)
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skos:notation
| - RIV/00216224:14310/07:00032275!RIV10-MSM-14310___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216224:14310/07:00032275
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - parametric and nonparametric and semiparametric discriminant analysis; kernel density estimation; product kernels; bandwidth choice; boundary kernels; variable bandwidth selector; elliptically contoured distribution; ROC analysis (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - TIES 2007, 18th annual meeting of the International Environmetrics Society
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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number of pages
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http://purl.org/ne...btex#hasPublisher
| - Ivana Horová, Jiří Hřebíček
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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