Regression spline smoothing using the minimum description length principle

被引:19
作者
Lee, TCM [1 ]
机构
[1] Colorado State Univ, Dept Stat, Ft Collins, CO 80523 USA
关键词
automatic knot selection; minimum description length; regression spline smoothing;
D O I
10.1016/S0167-7152(99)00191-1
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
One approach to estimating a function nonparametrically is to fit an rth-order regression spline to the noisy observations, and one important component of this approach is the choice of the number and the locations of the knots. This article proposes a new regression spline smoothing procedure which automatically chooses: (i) the order r of the regression spline being fitted; (ii) the number of the knots; and (iii) the locations of the knots. This procedure is based on the minimum description length principle, which is rarely applied to choose the amount of smoothing in nonparametric regression problems. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:71 / 82
页数:12
相关论文
共 10 条
[1]   Automatic Bayesian curve fitting [J].
Denison, DGT ;
Mallick, BK ;
Smith, AFM .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1998, 60 :333-350
[2]   Adapting to unknown smoothness via wavelet shrinkage [J].
Donoho, DL ;
Johnstone, IM .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1995, 90 (432) :1200-1224
[3]  
FRIEDMAN JH, 1989, TECHNOMETRICS, V31, P3, DOI 10.2307/1270359
[4]  
HALL P, 1988, BIOMETRIKA, V75, P705
[5]  
HASTIE T, 1989, TECHNOMETRICS, V31, P23, DOI 10.2307/1270360
[6]  
Hastie T., 1990, STAT SCI, DOI DOI 10.1214/SS/1177013604
[7]   Hybrid adaptive splines [J].
Luo, Z ;
Wahba, G .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1997, 92 (437) :107-116
[8]  
Rissanen J., 1989, STOCHASTIC COMPLEXIT
[9]   Nonparametric regression using Bayesian variable selection [J].
Smith, M ;
Kohn, R .
JOURNAL OF ECONOMETRICS, 1996, 75 (02) :317-343
[10]  
WAND MP, 1999, IN PRESS COMPUT STAT