calcAllocProb {batchmix}

Calculate allocation probabilities

Description

Calculate the empirical allocation probability for each class based on the sampled allocation probabilities.

Usage

calcAllocProb(mcmc_samples, burn = 0, method = "median")

Arguments

mcmc_samples

Output from “batchSemiSupervisedMixtureModel“.

burn

The number of samples to discard.

method

The point estimate to use. “method = 'mean'“ or “method = 'median'“. “'median'“ is the default.

Value

An N x K matrix of class probabilities.

Examples

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

# Initial labelling
labels <- c(
  rep(1, 10),
  sample(c(1, 2), size = 40, replace = TRUE),
  rep(2, 10),
  sample(c(1, 2), size = 40, replace = TRUE)
)

fixed <- c(rep(1, 10), rep(0, 40), rep(1, 10), rep(0, 40))

# Batch
batch_vec <- sample(seq(1, 5), replace = TRUE, size = 100)

# Sampling parameters
R <- 1000
thin <- 50

# MCMC samples and BIC vector
samples <- batchSemiSupervisedMixtureModel(X, R, thin, labels, fixed, batch_vec, "MVN")

# Burn in
burn <- 20
eff_burn <- burn / thin

# Probability across classes
probs <- calcAllocProb(samples, burn = burn)