Mixture Models: Building a Parameter Space
Methodology
2015-10-16 v1 Statistics Theory
Statistics Theory
Abstract
Despite the flexibility and popularity of mixture models, their associated parameter spaces are often difficult to represent due to fundamental identification problems. This paper looks at a novel way of representing such a space for general mixtures of exponential families, where the parameters are identifiable, interpretable, and, due to a tractable geometric structure, the space allows fast computational algorithms to be constructed.
Keywords
Cite
@article{arxiv.1510.04514,
title = {Mixture Models: Building a Parameter Space},
author = {Vahed Maroufy and Paul Marriott},
journal= {arXiv preprint arXiv:1510.04514},
year = {2015}
}