Fast Algorithm for Choosing Kernel Function Blur Coefficients in a Nonparametric Probability Density Estimate
- Autores: Lapko A.1,2, Lapko V.1,2
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Afiliações:
- Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences
- Reshetnev Siberian State University of Science and Technology
- Edição: Volume 61, Nº 6 (2018)
- Páginas: 540-545
- Seção: Article
- URL: https://journals.rcsi.science/0543-1972/article/view/246502
- DOI: https://doi.org/10.1007/s11018-018-1463-9
- ID: 246502
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Resumo
A fast algorithm for choosing the blurring coefficients of kernel functions for a nonparametric probability density estimate is proposed, and its properties are investigated. The technique of interval estimation of the standard deviation of the nonparametric statistics under consideration is considered.
Sobre autores
A. Lapko
Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences; Reshetnev Siberian State University of Science and Technology
Autor responsável pela correspondência
Email: lapko@icm.krasn.ru
Rússia, Krasnoyarsk; Krasnoyarsk
V. Lapko
Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences; Reshetnev Siberian State University of Science and Technology
Email: lapko@icm.krasn.ru
Rússia, Krasnoyarsk; Krasnoyarsk