estimates the variational posterior distribution of a GMM that aggregates a constrained collection of GMM. A lower bound is calculated and monitored at each iteration. This posterior can be used for various purposes (e.g. MC proposal distribution). It can be transformed using extractSimpleModel, outputing a GMM.
GMM made with the weighted sum of the collection of GMM to aggregate. a is used to model constraints between components in this GMM.
ncomp
number of components in the posterior.
thres
threshold for lower bound variations between 2 iterations. Convergence is decided if this variation is below thres.
maxit
if NULL, the stopping criterion is related to thres. If not NULL, maxit iterations are performed.
Value
estimated posterior with ncomp components.
References
Bruneau, P., Gelgon, M., and Picarougne, F. (2010) _Parsimonious reduction of Gaussian mixture
models with a variational-Bayes approach_, Pattern Recognition, Volume 43, Pages 850-858.