VICatMix (version 1.0)

runVICatMixAvg: runVICatMixAvg

Description

An extension of `runVICatMix` to incorporate model averaging/summarisation over multiple initialisations.

Usage

runVICatMixAvg(
  data,
  K,
  alpha,
  maxiter = 2000,
  tol = 5e-08,
  inits = 25,
  loss = "VoIcomp",
  parallel = FALSE,
  cores = getOption("mc.cores", 2L),
  verbose = FALSE
)

Value

A list with the following components: (maxNCat refers to the maximum number of categories for any covariate in the data)

labels_avg

A numeric N-vector listing the cluster assignments for the observations in the averaged model.

init_results

A list where each entry is the cluster assignments for one of the initialisations included in the model averaging.

Arguments

data

A data frame or data matrix with N rows of observations, and P columns of covariates.

K

Maximum number of clusters desired. Must be an integer greater than 1.

alpha

The Dirichlet prior parameter. Recommended to set this to a number < 1. Must be > 0.

maxiter

The maximum number of iterations for the algorithm. Default is 2000.

tol

A convergence parameter. Default is 5x10^-8.

inits

The number of initialisations included in the co-clustering matrix. Default is 25.

loss

The loss function to be used with the co-clustering matrix. Default is VoIcomp. Options are "VoIavg", "VoIcomp" and "medv".

parallel

Logical value indicating whether to run initialisations in parallel. Default is FALSE.

cores

User can specify number of cores for parallelisation if parallel = TRUE. Package automatically uses the user's parallel backend if one has already been registered.

verbose

Default FALSE. Set to TRUE to output ELBO values for each iteration.

See Also

runVICatMix

Examples

# example code
set.seed(20)
generatedData <- generateSampleDataBin(500, 4, c(0.1, 0.2, 0.3, 0.4), 100, 0)
result <- runVICatMixAvg(generatedData$data, 10, 0.01, inits = 10)

print(result$labels_avg)