Email this article Nonparametric Estimate of a Parzen-Type Probability Density with an Implicitly Specified Form of the Kernel
- Authors: Lapko A.V.1,2, Lapko V.A.1,2
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Affiliations:
- Institute of Computational Modelling, Siberian Branch of the Russian Academy of Sciences
- Siberian State Aerospace University
- Issue: Vol 59, No 6 (2016)
- Pages: 571-576
- Section: General Problems of Metrology and Measurement Technique
- URL: https://journals.rcsi.science/0543-1972/article/view/245355
- DOI: https://doi.org/10.1007/s11018-016-1010-5
- ID: 245355
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Abstract
A nonparametric estimate for the probability density is proposed with better approximation properties than the traditional Rosenblatt–Parzen statistics. The dependences of its properties on the form of the kernel function and on the formulas for the sampling interval for the random quantity are discussed.
About the authors
A. V. Lapko
Institute of Computational Modelling, Siberian Branch of the Russian Academy of Sciences; Siberian State Aerospace University
Author for correspondence.
Email: lapko@icm.krasn.ru
Russian Federation, Krasnoyarsk; Krasnoyarsk
V. A. Lapko
Institute of Computational Modelling, Siberian Branch of the Russian Academy of Sciences; Siberian State Aerospace University
Email: lapko@icm.krasn.ru
Russian Federation, Krasnoyarsk; Krasnoyarsk
