arXiv · 1509.07376
A hybrid sampler for Poisson-Kingman mixture models
Abstract
This paper concerns the introduction of a new Markov Chain Monte Carlo scheme for posterior sampling in Bayesian nonparametric mixture models with priors that belong to the general Poisson-Kingman class. We present a novel compact way of representing the infinite dimensional component of the model such that while explicitly representing this infinite component it has less memory and storage requirements than previous MCMC schemes. We describe comparative simulation results demonstrating the efficacy of the proposed MCMC algorithm against existing marginal and conditional MCMC samplers.
Explore related subjects
Keep this discovery
Maria Lomeli, Stefano Favaro, Yee Whye Teh. 2015-09-24. A hybrid sampler for Poisson-Kingman mixture models. https://arxiv.org/abs/1509.07376
Cite the original work for its findings. Save a collection to share your selection of sources.