EFFECT OF DATA INCOMPLETENESS ON THE APPROXIMATION PROPERTIES OF NONPARAMETRIC ESTIMATION OF THE TWO-DIMENSIONAL PROBABILITY DENSITY OF INDEPENDENT RANDOM VARIABLES
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, nonparametric estimate, asymptotic properties, independent random variables, data incompleteness
Subsection: ANALYSIS AND SYNTHESIS OF SIGNALS AND IMAGES
Abstract
Asymptotic properties of a nonparametric estimate of the two-dimensional probability density of independent random variables are studied. Based on these results, the dependence of its efficiency on data incompleteness in the initial statistical information is determined.
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