BCFM: Bayesian Clustering Factor Models

Implements the Bayesian Clustering Factor Models (BCFM) for simultaneous clustering and latent factor analysis of multivariate longitudinal data. The model accounts for within-cluster dependence through shared latent factors while allowing heterogeneity across clusters, enabling flexible covariance modeling in high-dimensional settings. Inference is performed using Markov chain Monte Carlo (MCMC) methods with computationally intensive steps implemented via 'Rcpp'. Model selection and visualization tools are provided. The methodology is described in Shin, Ferreira, and Tegge (2018) <doi:10.1002/sim.70350>.

Version:	1.0.0
Depends:	R (≥ 3.5)
Imports:	Rcpp, RcppArmadillo, dplyr, fastmatrix, ggplot2, grDevices, gridExtra, LaplacesDemon, mvtnorm, psych, RColorBrewer, stats, tidyr, ggpubr, tibble
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	knitr, rmarkdown
Published:	2026-02-10
DOI:	10.32614/CRAN.package.BCFM
Author:	Allison Tegge [aut], Marco Ferreira [aut], Hwasoo Shin [aut], Meriem Touami [aut, cre]
Maintainer:	Meriem Touami <meriemt at vt.edu>
BugReports:	https://github.com/ategge/BCFM/issues
License:	GPL (≥ 3)
URL:	https://github.com/ategge/BCFM
NeedsCompilation:	yes
SystemRequirements:	pandoc (>= 1.12.3) for building vignettes
Materials:	README
CRAN checks:	BCFM results

Documentation:

Reference manual:	BCFM.html , BCFM.pdf
Vignettes:	Getting Started with BCFM: A Complete Workflow (source, R code)

Downloads:

Package source:	BCFM_1.0.0.tar.gz
Windows binaries:	r-devel: BCFM_1.0.0.zip, r-release: BCFM_1.0.0.zip, r-oldrel: BCFM_1.0.0.zip
macOS binaries:	r-release (arm64): BCFM_1.0.0.tgz, r-oldrel (arm64): BCFM_1.0.0.tgz, r-release (x86_64): BCFM_1.0.0.tgz, r-oldrel (x86_64): BCFM_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=BCFM to link to this page.