Journal
STAT
Volume 2, Issue 1, Pages 61-71Publisher
WILEY
DOI: 10.1002/sta4.18
Keywords
Bayesian computing; longitudinal data analysis; mean field variational Bayes
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Funding
- Australian Postgraduate Award and Australian Research Council Discovery Project [DP110100061]
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We derive a variational inference procedure for approximate Bayesian inference in marginal longitudinal semi-parametric regression. Fitting and inference is much faster than existing Markov chain Monte Carlo approaches. Numerical studies indicate that the new methodology is very accurate for the class of models under consideration. Copyright (C) 2013 John Wiley & Sons, Ltd.
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