Schematic summary illustrating the HDP model framework.

<p>A graphical model provides a declarative representation of the HDPGMM. The figure shows a compact plate representation of the graphical model, in which plates (rounded rectangles) are used to group variables in a subgraph. Each subgraph in a plate is replicated a number of times as indicated by the label within the plate. The event in the sample is represented by , and the component for the sample is a multivariate Gaussian with proportion , mean and covariance matrix .s. Hyper-parameters that can be set are , , , , and as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003130#s4" target="_blank">Methods</a>. Given the declarative graphical model, standard and GPU-accelerated MCMC sampling algorithms can be used to implement the model as previously described <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003130#pcbi.1003130-Suchard1" target="_blank">[16]</a>.