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BCFM

Bayesian Clustering Factor Models (BCFM) for clustering and latent factor analysis of multivariate cross-sectional data.

Installation

You can install the development version of BCFM from GitHub with:

# install.packages("devtools")
devtools::install_github("ategge/BCFM", build_vignettes = TRUE)

Example

This is a basic example which shows you how to use BCFM:

library(BCFM)

# Load example data
data("sim.data", package = "BCFM")

# Specify variables to use for clustering
cluster.vars <- paste0("V", 1:20)

# Create output directory for results
# Use tempdir() for examples, or specify your own directory for real analyses
output_dir <- file.path(tempdir(), "BCFM_results")

# Run model selection
BCFM.model.selection(
  data = sim.data,
  cluster.vars = cluster.vars,   # Required parameter
  grouplist = 2:4,               # Try 2, 3, and 4 groups
  factorlist = 2:4,              # Try 2, 3, and 4 factors
  n.iter = 10000,                # Number of MCMC iterations
  burnin = 5000,                 # Burnin for Information Criterion calculations
  every = 10,                    # Progress update frequency
  cluster.size = 0.01,           # Minimum proportion required for each cluster (default 0.05)
  output_dir = output_dir,       # Specify where to save results
  seed = 123                     # Optional seed for reproducibility
)

# Results are saved in output_dir
# Load and visualize IC results
load(file.path(output_dir, "IC.Rdata"))
ggplot_IC(IC.matrix, factor_list = 2:4, group_list = 2:4)

# Load and visualize model results for 4 groups and 3 factors
load(file.path(output_dir, "results-covarianceF-g4-f3.Rdata"))
ggplot_latent.profiles(SDresult$Result)

Vignette

For a complete workflow tutorial, see the vignette:

# After installation with build_vignettes = TRUE
vignette("introduction-to-BCFM", package = "BCFM")

# Or browse all vignettes
browseVignettes("BCFM")

Features

Citation

If you use BCFM in your research, please cite:

[Add your citation here when you have a publication]

License

GPL-3

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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