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Bayesian Functional Data Analysis Using WinBUGS
- Source :
- Journal of Statistical Software, Vol 32, Iss 11 (2010)
- Publication Year :
- 2010
- Publisher :
- Foundation for Open Access Statistics, 2010.
-
Abstract
- 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) 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.
- Subjects :
- MCMC
mixed effects
covariance
smoothing
Statistics
HA1-4737
Subjects
Details
- Language :
- English
- ISSN :
- 15487660
- Volume :
- 32
- Issue :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- Journal of Statistical Software
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.90602dfc8293442e9ad8e2c7d6d393a8
- Document Type :
- article