Bayesian analysis for penalized spline regression using WinBUGS

Ciprian M. Crainiceanu, David Ruppert, M. P. Wand

Research output: Contribution to journalArticlepeer-review

193 Scopus citations


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.

Original languageEnglish (US)
JournalJournal of Statistical Software
StatePublished - 2005


  • MCMC
  • Semiparametric regression

ASJC Scopus subject areas

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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