REGRESSION ESTIMATE OF THE MULTIDIMENSIONAL PROBABILITY DENSITY AND ITS PROPERTIES
A. V. Lapko1,2, V. A. Lapko1,2
a:2:{s:4:"TEXT";s:285:"1Institute of Computational Modeling, Siberian Branch, Russian Academy of Sciences, Akademgorodok 50, building 44, Krasnoyarsk, 660036 Russia
2Reshetnev Siberian State Aerospace University, pr. im. Gazety “Krasnoyarskii rabochii” 31, Krasnoyarsk, 660014 Russia";s:4:"TYPE";s:4:"html";}
Keywords: probability density, regression estimate, large samples, asymptotic properties, a priori information
Subsection: ANALYSIS AND SYNTHESIS OF SIGNALS AND IMAGES
Abstract
A method of synthesis and analysis of regression estimate of the multidimensional probability density under conditions of a large volume of initial statistical data is proposed. Its asymptotic properties are investigated. On this basis, the relationship between the efficiency factor of the proposed estimate and the parameters of the procedure of expansion of initial data is established.
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