Bayesian Analysis for Penalized Spline Regression Using Win BUGS
Download the Paper Forward to a colleague
Abstract:
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 WinBUGS. MCMC mixing is substantially improved from the previous versions by using low{rank thin{plate splines instead of truncated polynomial basis. Simulation time per iteration is reduced 5 to 10 times using a computational trick.
Subject Area:
Computation, Statistical Models
Suggested Citation:
Ciprian M. Crainiceanu, David Ruppert, and M.P. Wand, "Bayesian Analysis for Penalized Spline Regression Using Win BUGS" (December 2007). Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 40.
http://www.bepress.com/jhubiostat/paper40