DESCRIPTION

Package: IMIFA
Type: Package
Date: 2023-12-12
Title: Infinite Mixtures of Infinite Factor Analysers and Related Models
Version: 2.2.0
Authors@R: c(person("Keefe", "Murphy", email = "keefe.murphy@mu.ie", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7709-3159")),
             person("Cinzia", "Viroli", email = "cinzia.viroli@unibo.it", role = "ctb", comment = c(ORCID = "0000-0002-3278-5266")),
             person("Isobel Claire", "Gormley", email = "claire.gormley@ucd.ie", role = "ctb", comment = c(ORCID = "0000-0001-7713-681X")))
Description: 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.
Depends: R (>= 4.0.0)
License: GPL (>= 3)
Encoding: UTF-8
URL: https://cran.r-project.org/package=IMIFA
BugReports: https://github.com/Keefe-Murphy/IMIFA
LazyData: true
Imports:
    matrixStats (>= 1.0.0),
    mclust (>= 5.4),
    mvnfast,
    Rfast (>= 1.9.8),
    slam,
    viridisLite
Suggests:
    gmp (>= 0.5-4),
    knitr,
    mcclust,
    rmarkdown,
    Rmpfr
RoxygenNote: 7.2.3
VignetteBuilder: knitr
Collate: 
    'MainFunction.R'
    'Diagnostics.R'
    'FullConditionals.R'
    'Gibbs_FA.R'
    'Gibbs_IFA.R'
    'Gibbs_IMFA.R'
    'Gibbs_IMIFA.R'
    'Gibbs_MFA.R'
    'Gibbs_MIFA.R'
    'Gibbs_OMFA.R'
    'Gibbs_OMIFA.R'
    'IMIFA.R'
    'PlottingFunctions.R'
    'SimulateData.R'
    'data.R'