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Erschienen in: Measurement Techniques 6/2017

03.10.2017 | GENERAL PROBLEMS OF METROLOGY AND MEASUREMENT TECHNIQUE

Analysis of Optimization Methods for Nonparametric Estimation of the Probability Density with Respect to the Blur Factor of Kernel Functions

verfasst von: A. V. Lapko, V. A. Lapko

Erschienen in: Measurement Techniques | Ausgabe 6/2017

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Abstract

The results of a comparison of the most common optimization methods for the nonparametric estimation of the probability density of Rosenblatt–Parzen are presented. To select the optimal values of the blur coefficients of kernel functions, minimum conditions for the standard deviation of the nonparametric estimate of the probability density and the maximum of the likelihood function are used.

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Metadaten
Titel
Analysis of Optimization Methods for Nonparametric Estimation of the Probability Density with Respect to the Blur Factor of Kernel Functions
verfasst von
A. V. Lapko
V. A. Lapko
Publikationsdatum
03.10.2017
Verlag
Springer US
Erschienen in
Measurement Techniques / Ausgabe 6/2017
Print ISSN: 0543-1972
Elektronische ISSN: 1573-8906
DOI
https://doi.org/10.1007/s11018-017-1228-x

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