IMIFA: Infinite Mixtures of Infinite Factor Analysers and Related Models

Provides flexible Bayesian estimation of Infinite Mixtures of Infinite Factor Analysers and related models, for nonparametrically clustering high-dimensional data, introduced by Murphy et al. (2020) <doi:10.1214/19-BA1179>. The IMIFA model conducts Bayesian nonparametric model-based clustering with factor analytic covariance structures without recourse to model selection criteria to choose the number of clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. Model-specific diagnostic tools are also provided, as well as many options for plotting results, conducting posterior inference on parameters of interest, posterior predictive checking, and quantifying uncertainty.

Version:	2.2.0
Depends:	R (≥ 4.0.0)
Imports:	matrixStats (≥ 1.0.0), mclust (≥ 5.4), mvnfast, Rfast (≥ 1.9.8), slam, viridisLite
Suggests:	gmp (≥ 0.5-4), knitr, mcclust, rmarkdown, Rmpfr
Published:	2023-12-12
DOI:	10.32614/CRAN.package.IMIFA
Author:	Keefe Murphy [aut, cre], Cinzia Viroli [ctb], Isobel Claire Gormley [ctb]
Maintainer:	Keefe Murphy <keefe.murphy at mu.ie>
BugReports:	https://github.com/Keefe-Murphy/IMIFA
License:	GPL (≥ 3)
URL:	https://cran.r-project.org/package=IMIFA
NeedsCompilation:	no
Citation:	IMIFA citation info
Materials:	README NEWS
In views:	Cluster
CRAN checks:	IMIFA results

Documentation:

Reference manual:	IMIFA.pdf
Vignettes:	Infinite Mixtures of Infinite Factor Analysers

Downloads:

Package source:	IMIFA_2.2.0.tar.gz
Windows binaries:	r-devel: IMIFA_2.2.0.zip, r-release: IMIFA_2.2.0.zip, r-oldrel: IMIFA_2.2.0.zip
macOS binaries:	r-release (arm64): IMIFA_2.2.0.tgz, r-oldrel (arm64): IMIFA_2.2.0.tgz, r-release (x86_64): IMIFA_2.2.0.tgz, r-oldrel (x86_64): IMIFA_2.2.0.tgz
Old sources:	IMIFA archive

Linking:

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