School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW 2522, Australia. e-mail: email@example.com
ON SEMIPARAMETRIC REGRESSION WITH O'SULLIVAN PENALIZED SPLINES
Article first published online: 6 MAY 2008
© 2008 Australian Statistical Publishing Association Inc.
Australian & New Zealand Journal of Statistics
Volume 50, Issue 2, pages 179–198, June 2008
How to Cite
Wand, M. P. and Ormerod, J. T. (2008), ON SEMIPARAMETRIC REGRESSION WITH O'SULLIVAN PENALIZED SPLINES. Australian & New Zealand Journal of Statistics, 50: 179–198. doi: 10.1111/j.1467-842X.2008.00507.x
- Issue published online: 8 JUL 2008
- Article first published online: 6 MAY 2008
Vol. 52, Issue 2, 239, Article first published online: 25 MAY 2010
- additive models;
- Markov chain Monte Carlo;
- mixed models;
- smoothing splines
An exposition on the use of O'Sullivan penalized splines in contemporary semiparametric regression, including mixed model and Bayesian formulations, is presented. O'Sullivan penalized splines are similar to P-splines, but have the advantage of being a direct generalization of smoothing splines. Exact expressions for the O'Sullivan penalty matrix are obtained. Comparisons between the two types of splines reveal that O'Sullivan penalized splines more closely mimic the natural boundary behaviour of smoothing splines. Implementation in modern computing environments such as Matlab, r and bugs is discussed.