Article (Scientific journals)
Robust specification of the roughness penalty prior distribution in spatially adaptive Bayesian P-splines models
Jullion, Astrid; Lambert, Philippe
2007In Computational Statistics and Data Analysis, 51, p. 2542-2558
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Abstract :
[en] The potential important role of the prior distribution of the roughness penalty parameter in the resulting smoothness of Bayesian Psplines models is considered. The recommended specification for that distribution yields models that can lack flexibility in specific circumstances. In such instances, these are shown to correspond to a frequentist P-splines model with a predefined and severe roughness penalty parameter, an obviously undesirable feature. It is shown that the specification of a hyperprior distribution for one parameter of that prior distribution provides the desired flexibility. Alternatively, a mixture prior can also be used. An extension of these two models by enabling adaptive penalties is provided. The posterior of all the proposed models can be quickly explored using the convenient Gibbs sampler.
Disciplines :
Mathematics
Author, co-author :
Jullion, Astrid
Lambert, Philippe  ;  Université de Liège - ULiège > Institut des sciences humaines et sociales > Méthodes quantitatives en sciences sociales
Language :
English
Title :
Robust specification of the roughness penalty prior distribution in spatially adaptive Bayesian P-splines models
Publication date :
2007
Journal title :
Computational Statistics and Data Analysis
ISSN :
0167-9473
eISSN :
1872-7352
Publisher :
Elsevier Science, Amsterdam, Netherlands
Volume :
51
Pages :
2542-2558
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
IAP research network nr P5/24
Funders :
Belgian State (Federal Office for Scientific, Technical and Cultural Affairs)
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since 29 September 2009

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