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Найдено документов в текущей БД: 3

    ANALYSIS OF OPTIMIZATION METHODS FOR NONPARAMETRIC ESTIMATION OF THE PROBABILITY DENSITY WITH RESPECT TO THE BLUR FACTOR OF KERNEL FUNCTIONS
/ A. V. Lapko, V. A. Lapko // Meas. Tech. - 2017. - Vol. 60, Is. 6. - P515-522, DOI 10.1007/s11018-017-1228-x. - Cited References:15 . - ISSN 0543-1972. - ISSN 1573-8906
РУБ Engineering, Multidisciplinary + Instruments & Instrumentation

Аннотация: The results of a comparison of the most common optimization methods for the nonparametric estimation of the probability density of Rosenblatt-Parzen are presented. To select the optimal values of the blur coefficients of kernel functions, minimum conditions for the standard deviation of the nonparametric estimate of the probability density and the maximum of the likelihood function are used.

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Держатели документа:
Russian Acad Sci, Siberian Branch, Inst Computat Modeling, Krasnoyarsk, Russia.
Reshetnev Siberian State Univ Sci & Technol, Krasnoyarsk, Russia.

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.
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    Fast Algorithm for Choosing Kernel Function Blur Coefficients in a Nonparametric Probability Density Estimate
/ A. V. Lapko, V. A. Lapko // Meas. Tech. - 2018. - Vol. 61, Is. 6. - P540-545, DOI 10.1007/s11018-018-1463-9. - Cited References:16. - This study was supported by the Russian Foundation for Basic Research (Grant No. 18-01-00251). . - ISSN 0543-1972. - ISSN 1573-8906
РУБ Engineering, Multidisciplinary + Instruments & Instrumentation

Аннотация: A fast algorithm for choosing the blurring coefficients of kernel functions for a nonparametric probability density estimate is proposed, and its properties are investigated. The technique of interval estimation of the standard deviation of the nonparametric statistics under consideration is considered.

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Scopus

Держатели документа:
Russian Acad Sci, Inst Computat Modeling, Siberian Branch, Krasnoyarsk, Russia.
Reshetnev Siberian State Univ Sci & Technol, Krasnoyarsk, Russia.

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.; Russian Foundation for Basic Research [18-01-00251]
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    Fast Algorithm for Choosing Blur Coefficients in Multidimensional Kernel Probability Density Estimates
/ A. V. Lapko, V. A. Lapko // Meas. Tech. - 2019. - Vol. 61, Is. 10. - P979-986, DOI 10.1007/s11018-019-01536-x. - Cited References:17. - This work was supported by the Russian Foundation for Basic Research (Grant No. 18-01-00251). . - ISSN 0543-1972. - ISSN 1573-8906
РУБ Engineering, Multidisciplinary + Instruments & Instrumentation

Аннотация: A method is proposed for quickly choosing the blur coefficients of kernel functions in a non-parametric estimate of a multidimensional probability density of Rosenblatt-Parzen type. The technique is based on the analysis of the asymptotic properties of a multidimensional probability density estimate. The properties of the fast algorithm for choosing the blur coefficients of a kernel probability density estimate are investigated.

WOS,
Смотреть статью,
Scopus,
РИНЦ

Держатели документа:
Russian Acad Sci, Siberian Branch, Inst Computat Modeling, Krasnoyarsk, Russia.
Reshetnev Siberian State Univ Sci & Technol, Krasnoyarsk, Russia.

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.; Russian Foundation for Basic Research [18-01-00251]
Найти похожие