Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
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Authors: Ciprian M. Crainiceanu, A. Jeffrey Goldsmith
Title: Bayesian Functional Data Analysis Using WinBUGS
Abstract: We provide user friendly software for Bayesian analysis of functional data models using pkg{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) mixed model representation of functional models, which provides a modular approach to model extension; and (3) 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.

Page views:: 11161. Submitted: 2009-07-29. Published: 2010-01-05.
Paper: Bayesian Functional Data Analysis Using WinBUGS     Download PDF (Downloads: 12102)
Supplements:
Bayes_FDA.zip: WinBUGS/R source code Download (Downloads: 1377; 1MB)
v32i11.txt: WinBUGS example code from the paper Download (Downloads: 1632; 9KB)
DOI: 10.18637/jss.v032.i11

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.