Title :
On nonparametric kernel estimation of nonlinear functionals
Author :
Ryumkin, Valeri I.
Author_Institution :
Tomsk State Univ., Russia
fDate :
26 June-3 July 2004
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;
Conference_Titel :
Science and Technology, 2004. KORUS 2004. Proceedings. The 8th Russian-Korean International Symposium on
Print_ISBN :
0-7803-8383-4
DOI :
10.1109/KORUS.2004.1555582
