TY - JOUR
T1 - Bayesian analysis for penalized spline regression using WinBUGS
AU - Crainiceanu, Ciprian M.
AU - Ruppert, David
AU - Wand, M. P.
PY - 2005
Y1 - 2005
N2 - Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in Win BUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.
AB - Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in Win BUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.
KW - MCMC
KW - Semiparametric regression
UR - http://www.scopus.com/inward/record.url?scp=27544482613&partnerID=8YFLogxK
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U2 - 10.18637/jss.v014.i14
DO - 10.18637/jss.v014.i14
M3 - Article
AN - SCOPUS:27544482613
SN - 1548-7660
VL - 14
JO - Journal of Statistical Software
JF - Journal of Statistical Software
ER -