Package: IMIFA 2.2.0

IMIFA: 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. (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.

Authors:Keefe Murphy [aut, cre], Cinzia Viroli [ctb], Isobel Claire Gormley [ctb]

IMIFA_2.2.0.tar.gz
IMIFA_2.2.0.zip(r-4.5)IMIFA_2.2.0.zip(r-4.4)IMIFA_2.2.0.zip(r-4.3)
IMIFA_2.2.0.tgz(r-4.4-any)IMIFA_2.2.0.tgz(r-4.3-any)
IMIFA_2.2.0.tar.gz(r-4.5-noble)IMIFA_2.2.0.tar.gz(r-4.4-noble)
IMIFA_2.2.0.tgz(r-4.4-emscripten)IMIFA_2.2.0.tgz(r-4.3-emscripten)
IMIFA.pdf |IMIFA.html✨
IMIFA/json (API)
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Bug tracker:https://github.com/keefe-murphy/imifa/issues

On CRAN:

bayesian-nonparametricsdimension-reductionfactor-analysisgaussian-mixture-modelmodel-based-clustering

34 exports 7 stars 1.42 score 12 dependencies 54 scripts 597 downloads

Last updated 9 months agofrom:bb2611691c. Checks:OK: 7. Indexed: yes.

Exports:bnpControlexp_ltrgammaG_calibrateG_expectedG_priorDensityG_varianceget_IMIFA_resultsgumbel_maxheat_legendIMIFA_newsis.colsis.posi_defLedermannmat2colsmcmc_IMIFAMGP_checkmgpControlmixfaControlpareto_scalePGMM_dfreeplot_colspost_conf_matProcrustespsi_hyperrDirichletrltrgammascores_MAPshift_GAshow_digitshow_IMIFA_digitsim_IMIFA_datasim_IMIFA_modelstoreControlZsimilarity

Dependencies:BHmatrixStatsmclustmvnfastRcppRcppArmadilloRcppGSLRcppParallelRcppZigguratRfastslamviridisLite