Variational Bayes for Elaborate Distributions
MATTHEW P. WAND, John T. Ormerod, Simone A. Padoan, Rudolf Konrad Fruhwirth · Research Online (University of Wollongong) · 2010
We develop strategies for variational Bayes approximate inference for models containing elaborate distributions. Such models suffer from the difficulty that the parameter updates do not admit closed form solutions. We circumvent this problem through a combination of (a) specially tailored auxiliary variables, (b) univariate quadrature schemes and (c) finite mixture approximations of troublesome density functions. An accuracy assessment is conducted and the new methodology is illustrated in an application.