On local smoothing of nonparametric curve estimators

被引:30
作者
Fan, JQ
Hall, P
Martin, MA
Patil, P
机构
[1] AUSTRALIAN NATL UNIV, DEPT STAT, CANBERRA, ACT 0200, AUSTRALIA
[2] AUSTRALIAN NATL UNIV, CTR MATH & APPLICAT, CANBERRA, ACT 0200, AUSTRALIA
[3] UNIV BIRMINGHAM, SCH MATH & STAT, BIRMINGHAM B15 2TT, W MIDLANDS, ENGLAND
关键词
adaptive smoothing; bandwidth; cross-validation; curves estimation; density estimation; kernel methods; local smoothing; nonparametric regression; wavelets;
D O I
10.2307/2291403
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 develop new local versions of familiar smoothing methods; such as cross-validation and smoothed cross-validation, in the contexts of density estimation and regression. These new methods are locally adaptive in the sense that they capture smooth local fluctuations in the curve by using smoothly varying bandwidths that change as the character of the curve changes. Moreover, the new methods are accurate, easy to apply, and computationally expedient.
引用
收藏
页码:258 / 266
页数:9
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