bcm-class {tip}

Bayesian Clustering Model (bcm) S4 class.

Description

An S4 class to store the results of the Gibbs sampler.

Value

An object of class bcm.

Slots

n

Positive integer: the sample size (i.e., the number of subjects).

burn

Non-negative integer: the number of burn-in iterations in the Gibbs sampler.

samples

Positive integer: the number of sampling iterations in the Gibbs sampler.

posterior_assignments

List of vectors of positive integers: a list of vectors of cluster assignments (i.e., positive integers) for each sampling iteration in the Gibbs sampler.

posterior_similarity_matrix

Matrix: a matrix where the (i,j)th element is the posterior probability that subject i and subject j belong to the same cluster.

posterior_number_of_clusters

Vector of positive integers: each vector element is the number of clusters after posterior sampling for each sampling iteration in the Gibbs sampler.

prior_name

Character: the name of the prior used.

likelihood_name

Character: the name of the likelihood used.