Estimating the Number of Components in Finite Mixture Models via Variational Approximation

arXiv:2404.16746v1 Announce Type: cross
Abstract: This work introduces a new method for selecting the number of components in finite mixture models (FMMs) using variational Bayes, inspired by the large-sample properties of the Evidence Lower Bound (ELBO) derived from mean-field (MF) variational approximation. Specifically, we establish matching upper and lower bounds for the ELBO without assuming conjugate priors, suggesting the consistency of model selection for FMMs based on maximizing the ELBO. As a by-product of our proof, we demonstrate that the …

abstract approximation arxiv bayes components evidence math.st mean sample stat.me stat.ml stat.th type via work