Abstract
The smoothing spline method is used to fit a curve to a noisy data set, where selection of the smoothing parameter is essential. An adaptive Cp criterion (Chen and Huang 2011) based on the Stein’s unbiased risk estimate has been proposed to select the smoothing parameter, which not only considers the usual effective degrees of freedom but also takes into account the selection variability. The resulting fitted curve has been shown to be superior and more stable than commonly used selection criteria and possesses the same asymptotic optimality as Cp. In this paper, we further discuss some characteristics on the selection of smoothing parameter, especially for the selection variability.
| Original language | English |
|---|---|
| Pages (from-to) | 1307-1317 |
| Number of pages | 11 |
| Journal | Communications in Statistics - Theory and Methods |
| Volume | 47 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2018 Mar 19 |
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All Science Journal Classification (ASJC) codes
- Statistics and Probability
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Some characteristics on the selection of spline smoothing parameter. / Chen, Chun Shu; Huang, Yi Tsz.
In: Communications in Statistics - Theory and Methods, Vol. 47, No. 6, 19.03.2018, p. 1307-1317.Research output: Contribution to journal › Article
TY - JOUR
T1 - Some characteristics on the selection of spline smoothing parameter
AU - Chen, Chun Shu
AU - Huang, Yi Tsz
PY - 2018/3/19
Y1 - 2018/3/19
N2 - The smoothing spline method is used to fit a curve to a noisy data set, where selection of the smoothing parameter is essential. An adaptive Cp criterion (Chen and Huang 2011) based on the Stein’s unbiased risk estimate has been proposed to select the smoothing parameter, which not only considers the usual effective degrees of freedom but also takes into account the selection variability. The resulting fitted curve has been shown to be superior and more stable than commonly used selection criteria and possesses the same asymptotic optimality as Cp. In this paper, we further discuss some characteristics on the selection of smoothing parameter, especially for the selection variability.
AB - The smoothing spline method is used to fit a curve to a noisy data set, where selection of the smoothing parameter is essential. An adaptive Cp criterion (Chen and Huang 2011) based on the Stein’s unbiased risk estimate has been proposed to select the smoothing parameter, which not only considers the usual effective degrees of freedom but also takes into account the selection variability. The resulting fitted curve has been shown to be superior and more stable than commonly used selection criteria and possesses the same asymptotic optimality as Cp. In this paper, we further discuss some characteristics on the selection of smoothing parameter, especially for the selection variability.
UR - http://www.scopus.com/inward/record.url?scp=85029689624&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85029689624&partnerID=8YFLogxK
U2 - 10.1080/03610926.2017.1317808
DO - 10.1080/03610926.2017.1317808
M3 - Article
AN - SCOPUS:85029689624
VL - 47
SP - 1307
EP - 1317
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
SN - 0361-0926
IS - 6
ER -