Reference : Robust specification of the roughness penalty prior distribution in spatially adaptiv...
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Mathematics
Robust specification of the roughness penalty prior distribution in spatially adaptive Bayesian P-splines models
Jullion, Astrid [ > > ]
Lambert, Philippe mailto [Université de Liège - ULg > Institut des sciences humaines et sociales > Méthodes quantitatives en sciences sociales >]
Computational Statistics & Data Analysis
Elsevier Science
Yes (verified by ORBi)
The Netherlands
[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.
Belgian State (Federal Office for Scientific, Technical and Cultural Affairs)
IAP research network nr P5/24

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