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.
Package details |
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Author | Keefe Murphy [aut, cre] (<https://orcid.org/0000-0002-7709-3159>), Cinzia Viroli [ctb] (<https://orcid.org/0000-0002-3278-5266>), Isobel Claire Gormley [ctb] (<https://orcid.org/0000-0001-7713-681X>) |
Maintainer | Keefe Murphy <keefe.murphy@mu.ie> |
License | GPL (>= 3) |
Version | 2.2.0 |
URL | https://cran.r-project.org/package=IMIFA |
Package repository | View on CRAN |
Installation |
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