Nonparametric Estimation of the Quadratic Functional of a Multimodal Probability Density
- 作者: Lapko A.1,2, Lapko V.1,2
-
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 9 (2019)
- 页面: 769-775
- 栏目: Article
- URL: https://journals.rcsi.science/0543-1972/article/view/246777
- DOI: https://doi.org/10.1007/s11018-019-01693-z
- ID: 246777
如何引用文章
详细
A nonparametric method for estimating the mean square functional of a multimodal probability density of a one-dimensional random variable is examined. The proposed method is based on using the Sturgis and Heinhold–Gaede formulas and an optimum sampling procedure for sampling a range of values of random quantities. This method is compared with the traditional approach based on choosing a spread coefficient using the condition for the maximum of the likelihood function. The conditions for competence of this method are determined.
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