dis_mat_example

A dissimilarity matrix computed with <code><a href="/link/stats%3A%3Adist()?package=DPCD&version=0.0.1" data-mini-rdoc="DPCD::stats::dist()">stats::dist()</a></code> on a simulated dataset.

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

dis_mat_example function

An object of class <code><a href="/link/stats%3A%3Adist()?package=DPCD&version=0.0.1" data-mini-rdoc="DPCD::stats::dist()">stats::dist()</a></code> containing pairwise similarities for (\(n = 20\)) objects.

Format

A dissimilarity matrix computed with <code><a href='https://rdrr.io/r/stats/dist.html'>stats::dist()</a></code> on a simulated dataset.

Dissimilarity Matrix Example — dis_mat_example

An object of class <code><a href='https://rdrr.io/r/stats/dist.html'>stats::dist()</a></code> containing pairwise similarities for (\(n = 20\)) objects.

dis_mat_example: Dissimilarity Matrix Example

Description

Usage

Arguments

Format

Details