Recurrent nonparametric estimation of functions from functionals of multidimensional density and their derivatives

被引：7
作者：
Kitaeva, A. V. [1 ]
Koshkin, G. M. [1 ]
机构：
[1] Tomsk VV Kuibyshev State Univ, Tomsk Polytechn Univ, Dept Informatizat Problems, Tomsk Sci Ctr,Russian Acad Sci, Tomsk 634050, Russia
来源：
AUTOMATION AND REMOTE CONTROL | 2009年 / 70卷 / 03期
关键词：
REGRESSION FUNCTION; CONVERGENCE; CLASSIFICATION; CONSISTENCY;
D O I：
10.1134/S0005117909030060
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Recurrent kernel estimates of functions are considered, which depend on functionals of the multidimensional distribution density and their derivatives, and also their piecewise smooth approximations. The principal part of a mean square error of estimates is found. The suggested approach enables estimating from unique positions, for example, the production function and its characteristics. The comparison is performed of recurrent and common estimates both in asymptotics and at finite volumes of samples.
引用
收藏
页码：389 / 407
页数：19
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