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    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.