Derivation of equivalent kernel for general spline smoothing: a systematic approach

被引:7
作者
Abramovich, F [1 ]
Grinshtein, V
机构
[1] Tel Aviv Univ, Raymond & Beverly Sackler Fac Exact Sci, Dept Stat & Operat Res, IL-69978 Ramat Aviv, Israel
[2] Tel Aviv Univ, Raymond & Beverly Sackler Fac Exact Sci, Dept Math, IL-69978 Ramat Aviv, Israel
[3] Univ Bristol, Sch Math, Bristol BS8 1TH, Avon, England
关键词
Green's function; L-smoothing spline; nonparametric regression; variable smoothing parameter; Wentzel-Kramers-Brillouin method;
D O I
10.2307/3318440
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We consider first the spline smoothing nonparametric estimation with variable smoothing parameter and arbitrary design density function and show that the corresponding equivalent kernel can be approximated by the Green function of a certain linear differential operator. Furthermore, we propose to use the Standard (in applied mathematics and engineering) method for asymptotic solution of linear differential equations, known as the Wentzel-Kramers-Brillouin method, for systematic derivation of an asymptotically equivalent kernel in this general case. The corresponding results for polynomial splines are a special case of the general solution. Then, we show how these ideas can be directly extended to the very general L-spline smoothing.
引用
收藏
页码:359 / 379
页数:21
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