DocumentCode
445746
Title
On nonparametric kernel estimation of nonlinear functionals
Author
Ryumkin, Valeri I.
Author_Institution
Tomsk State Univ., Russia
Volume
2
fYear
2004
fDate
26 June-3 July 2004
Firstpage
172
Abstract
In this paper the truncated approximation for nonparametric functional estimate is proposed. The mean square convergence of this approximation from dependent sample satisfying strong mixing condition is proved. The main part of asymptotic mean square error for the proposed modification of kernel regression estimate is found. These results are used for functional scaling in economics, ecology and geology.
Keywords
convergence of numerical methods; ecology; economics; geology; mean square error methods; nonlinear functions; nonparametric statistics; regression analysis; asymptotic mean square error; ecology; economics; functional scaling; geology; kernel regression estimate; mean square convergence; nonlinear functionals; nonparametric kernel estimation; truncated approximation; Convergence; Covariance matrix; Density functional theory; Environmental factors; Geology; Kernel; Mean square error methods; Random variables; State estimation; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Science and Technology, 2004. KORUS 2004. Proceedings. The 8th Russian-Korean International Symposium on
Print_ISBN
0-7803-8383-4
Type
conf
DOI
10.1109/KORUS.2004.1555582
Filename
1555582
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