getSampledClusterMeans {batchmix}

Get sampled cluster means

Description

Given an array of sampled cluster means from the “mixtureModel“ function, acquire a tidy version ready for “ggplot2“ use.

Usage

getSampledClusterMeans(
  sampled_cluster_means,
  K = dim(sampled_cluster_means)[2],
  P = dim(sampled_cluster_means)[1],
  R = dim(sampled_cluster_means)[3],
  thin = 1
)

Arguments

sampled_cluster_means

A 3D array of sampled cluster means.

K

The number of clusters present. Defaults to the number of columns in the batch mean matrix from the first sample.

P

The dimension of the batch mean shifts. Defaults to the number of rows in the batch mean matrix from the first sample.

R

The number of iterations run. Defaults to the number of slices in the sampled batch mean array.

thin

The thinning factor of the sampler. Defaults to 1.

Value

A data.frame of three columns; the parameter, the sampled value and the iteration.

Examples

# Data in matrix format
X <- matrix(c(rnorm(100, 0, 1), rnorm(100, 3, 1)), ncol = 2, byrow = TRUE)

# Observed batches represented by integers
batch_vec <- sample(seq(1, 5), size = 100, replace = TRUE)

# MCMC iterations (this is too low for real use)
R <- 100
thin <- 5

# MCMC samples
samples <- runBatchMix(X, R, thin, batch_vec, "MVN")

batch_shift_df <- getSampledClusterMeans(samples$means, R = R, thin = thin)