Email this article Nonparametric Estimation of the Quadratic Functional of a Multimodal Probability Density
- Authors: Lapko A.V.1,2, Lapko V.A.1,2
-
Affiliations:
- Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences
- Reshetnev Siberian State University of Science and Technology
- Issue: Vol 62, No 9 (2019)
- Pages: 769-775
- Section: Article
- URL: https://journals.rcsi.science/0543-1972/article/view/246777
- DOI: https://doi.org/10.1007/s11018-019-01693-z
- ID: 246777
Cite item
Open Access
Access granted
Subscription Access
Abstract
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.
About the authors
A. V. Lapko
Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences; Reshetnev Siberian State University of Science and Technology
Author for correspondence.
Email: lapko@icm.krasn.ru
Russian Federation, Krasnoyarsk; Krasnoyarsk
V. A. 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
Russian Federation, Krasnoyarsk; Krasnoyarsk
