mcmc_example

<p>Posterior samples returned by <code>run_dpcd()</code> after fitting an Equal Spherical (ES) model to simulated dissimilarities.</p>

datasets

A Bayesian hierarchical model for clustering dissimilarity data using the Dirichlet process. The latent configuration of objects and the number of clusters are automatically inferred during the fitting process. The package supports multiple models which are available to detect clusters of various shapes and sizes using different covariance structures. Additional functions are included to ensure adequate model fits through prior and posterior predictive checks.

Samuel Morrissette

DPCD

Dirichlet Process Clustering with Dissimilarities

Sam Morrissette

mcmc_example function

<p>An object of class <code>mcmc</code> containing posterior draws for the monitored parameters from the DPCD model fit. It contains 4,000 rows (MCMC iterations) and 110 columns.</p>

mcmc_example: MCMC Example Output

Description

Usage

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Details