Отправить статью по E-mail Selection of the Blur Coefficient for Probability Density Kernel Estimates Under Conditions of Large Samples
- Авторы: Lapko A.1,2, Lapko V.1,2
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Учреждения:
- Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences
- Reshetnev Siberian State University of Science and Technology
- Выпуск: Том 62, № 5 (2019)
- Страницы: 383-389
- Раздел: General Problems of Metrology and Measurement Technique
- URL: https://journals.rcsi.science/0543-1972/article/view/246718
- DOI: https://doi.org/10.1007/s11018-019-01634-w
- ID: 246718
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Аннотация
A fast algorithm is proposed for choosing the blur factors of kernel functions of a non-parametric probability density estimate under conditions of large-scale statistical data. It is shown that the basis of the algorithm is the result of a study of the asymptotic properties of a new kernel probability density estimate. The properties of the developed algorithm are analyzed and the method of its application is formulated.
Об авторах
A. Lapko
Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences; Reshetnev Siberian State University of Science and Technology
Автор, ответственный за переписку.
Email: lapko@icm.krasn.ru
Россия, 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
Россия, Krasnoyarsk; Krasnoyarsk
