VBmix (version 0.2.8)

mmppca: mmppca

Description

estimates the variational posterior distribution of a MPPCA that aggregates a collection of input MPPCA models. 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 mppcaToGmm and subMppca, outputing a GMM. The maximal rank of output factor matrices is determined by the inputs.

Usage

mmppca(mods, ncomp, thres = 0.1, maxit = NULL)

Arguments

mods

input MPPCA that concatenates the set of components to aggregate.

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 MPPCA with ncomp components.

References

Bruneau, P., Gelgon, M. and Picarougne, F. (2010) _Aggregation of probabilistic PCA mixtures with a variational-Bayes technique over parameters_, ICPR'10.

Bruneau, P., Gelgon, M. and Picarougne, F. (2011) _Component-level aggregation of probabilistic PCA mixtures using variational-Bayes_, Tech Report, http://hal.archives-ouvertes.fr/docs/00/56/72/99/PDF/techrep.pdf.

See Also

newMppca mppca subMppca

Examples

temp <- newMppca()
for(i in 1:10) temp <- appendToMppca(temp, pcapen[[i]])
temp2 <- mmppca(temp, 100, maxit=30)