电邮这篇文章 Selection of the Blur Coefficient for Probability Density Kernel Estimates Under Conditions of Large Samples
- 作者: Lapko A.1,2, Lapko V.1,2
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隶属关系:
- Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences
- Reshetnev Siberian State University of Science and Technology
- 期: 卷 62, 编号 5 (2019)
- 页面: 383-389
- 栏目: 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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详细
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.
作者简介
A. Lapko
Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences; Reshetnev Siberian State University of Science and Technology
编辑信件的主要联系方式.
Email: lapko@icm.krasn.ru
俄罗斯联邦, 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
俄罗斯联邦, Krasnoyarsk; Krasnoyarsk
