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:1701.07010v4>. 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, and quantifying uncertainty.
Version: | 2.0.0 |
Depends: | R (≥ 3.3.0) |
Imports: | matrixStats, mclust (≥ 5.1), mvnfast, Rfast (≥ 1.8.4), slam, viridis |
Suggests: | gmp, knitr, mcclust, methods, rmarkdown, Rmpfr |
Published: | 2018-05-01 |
Author: | Keefe Murphy [aut, cre], Isobel Claire Gormley [ctb], Cinzia Viroli [ctb] |
Maintainer: | Keefe Murphy <keefe.murphy at ucd.ie> |
BugReports: | https://github.com/Keefe-Murphy/IMIFA |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://cran.r-project.org/package=IMIFA |
NeedsCompilation: | no |
Citation: | IMIFA citation info |
Materials: | README NEWS |
In views: | Cluster |
CRAN checks: | IMIFA results |
Reference manual: | IMIFA.pdf |
Vignettes: |
Infinite Mixtures of Infinite Factor Analysers |
Package source: | IMIFA_2.0.0.tar.gz |
Windows binaries: | r-devel: IMIFA_2.0.0.zip, r-release: IMIFA_2.0.0.zip, r-oldrel: IMIFA_2.0.0.zip |
OS X binaries: | r-release: IMIFA_2.0.0.tgz, r-oldrel: IMIFA_2.0.0.tgz |
Old sources: | IMIFA archive |
Please use the canonical form https://CRAN.R-project.org/package=IMIFA to link to this page.