cls.draw2: Sample of Clusterings from Posterior Distribution of Bayesian...

In mcclust: Process an MCMC Sample of Clusterings

Sample of Clusterings from Posterior Distribution of Bayesian Cluster Model

Description

Output of a Dirichlet process mixture model with normal components fitted to the data set Ysim2. True clusters are given by rep(1:8,each =50).

Usage

data(cls.draw2)

Format

matrix with 500 rows and 400 columns. Each row contains a clustering of the 400 observations.

Source

Fritsch, A. and Ickstadt, K. (2009) An improved criterion for clustering based on the posterior similarity matrix, Bayesian Analysis, accepted.

mcclust documentation built on May 2, 2022, 5:05 p.m.