IMIFA: Fitting, Diagnostics, and Plotting Functions for 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. (2017) <arXiv:1701.07010>. 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 and conducting posterior inference on parameters of interest.

Version: 1.3.1
Depends: R (≥ 3.3.2)
Imports: abind, e1071, graphics, grDevices, matrixStats, mclust, mvnfast, plotrix, Rfast, slam, stats, utils, viridis
Suggests: Rmpfr, gmp, knitr, methods, rmarkdown
Published: 2017-07-07
Author: Keefe Murphy [aut, cre], Isobel Claire Gormley [ctb], Cinzia Viroli [ctb]
Maintainer: Keefe Murphy <keefe.murphy at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README NEWS
In views: Cluster
CRAN checks: IMIFA results


Reference manual: IMIFA.pdf
Vignettes: Infinite Mixtures of Infinite Factor Analysers
Package source: IMIFA_1.3.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: IMIFA_1.3.1.tgz
OS X Mavericks binaries: r-oldrel: IMIFA_1.3.1.tgz
Old sources: IMIFA archive


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