Direct Determination of Smoothing Parameter for Penalized Spline Regression
Author
Source
Journal of Probability and Statistics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-22
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Penalized spline estimator is one of the useful smoothing methods.
To construct the estimator, having goodness of fit and smoothness, the smoothing parameter should be appropriately selected.
The purpose of this paper is to select the smoothing parameter using the asymptotic property of the penalized splines.
The new smoothing parameter selection method is established in the context of minimization asymptotic form of MISE of the penalized splines.
The mathematical and the numerical properties of the proposed method are studied.
First we organize the new method in univariate regression model.
Next we extend to the additive models.
A simulation study to confirm the efficiency of the proposed method is addressed.
American Psychological Association (APA)
Yoshida, Takuma. 2014. Direct Determination of Smoothing Parameter for Penalized Spline Regression. Journal of Probability and Statistics،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1042812
Modern Language Association (MLA)
Yoshida, Takuma. Direct Determination of Smoothing Parameter for Penalized Spline Regression. Journal of Probability and Statistics No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1042812
American Medical Association (AMA)
Yoshida, Takuma. Direct Determination of Smoothing Parameter for Penalized Spline Regression. Journal of Probability and Statistics. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1042812
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1042812