Title
P-splines regression smoothing and difference type of penalty
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
London ,
Subject
Mathematics
Computer. Automation
Source (journal)
Statistics and computing. - London
Volume/pages
20(2010) :4 , p. 499-511
ISSN
0960-3174
ISI
000281983200009
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Abstract
P-splines regression provides a flexible smoothing tool. In this paper we consider difference type penalties in a context of nonparametric generalized linear models, and investigate the impact of the order of the differencing operator. Minimizing Akaikes information criterion we search for a possible best data-driven value of the differencing order. Theoretical derivations are established for the normal model and provide insights into a possible optimal choice of the differencing order and its interrelation with other parameters. Applications of the selection procedure to non-normal models, such as Poisson models, are given. Simulation studies investigate the performance of the selection procedure and we illustrate its use on real data examples.
E-info
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