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Keywords:

  • Bayesian computing;
  • longitudinal data analysis;
  • mean field variational Bayes

We derive a variational inference procedure for approximate Bayesian inference in marginal longitudinal semiparametric 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 © 2013 John Wiley & Sons Ltd