We provide user friendly software for Bayesian analysis of Functional Data Models using WinBUGS 1.4. The excellent properties of Bayesian analysis in this context are due to: 1) dimensionality reduction, which leads to low dimensional projection bases; 2)the mixed model representation of functional models, which provides a modular approach to model extension; and 3) the orthogonality of the principal component bases, which contributes to excellent chain convergence and mixing properties. Our paper provides one more, essential, reason for using Bayesian analysis for Functional models: the existence of software.
Crainiceanu, Ciprian M. and Goldsmith, A. Jeffrey, "BAYESIAN FUNCTIONAL DATA ANALYSIS USING WinBUGS" (November 2009). Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 195.
Accepted by Journal of Statistical Software