person("Cinzia", "Viroli", email = "cinzia.viroli@unibo.it", role = "ctb"),
person("Isobel Claire", "Gormley", email = "claire.gormley@ucd.ie", role = "ctb"))
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. (2018) <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, posterior predictive checking, and quantifying uncertainty.

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. (2019) <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.
Imports: matrixStats, mclust (>= 5.1), mvnfast, Rfast (>= 1.9.4), slam,

Authors@R: c(person("Keefe", "Murphy", email = "keefe.murphy@ucd.ie", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7709-3159")),
Imports: matrixStats, mclust (>= 5.1), mvnfast, Rfast (>= 1.9.8), slam,
Suggests: gmp, knitr, mcclust, rmarkdown, Rmpfr
Author: Keefe Murphy [aut, cre] (<https://orcid.org/0000-0002-7709-3159>),

Authors@R: c(person("Keefe", "Murphy", email = "keefe.murphy@mu.ie", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7709-3159")),
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.
Imports: matrixStats (>= 0.53.1), mclust (>= 5.4), mvnfast, Rfast (>=
Suggests: gmp (>= 0.5-4), knitr, mcclust, rmarkdown, Rmpfr