Package: AntMAN 1.1.0

AntMAN: Anthology of Mixture Analysis Tools

Fits finite Bayesian mixture models with a random number of components. The MCMC algorithm implemented is based on point processes as proposed by Argiento and De Iorio (2019) <arxiv:1904.09733> and offers a more computationally efficient alternative to reversible jump. Different mixture kernels can be specified: univariate Gaussian, multivariate Gaussian, univariate Poisson, and multivariate Bernoulli (latent class analysis). For the parameters characterising the mixture kernel, we specify conjugate priors, with possibly user specified hyper-parameters. We allow for different choices for the prior on the number of components: shifted Poisson, negative binomial, and point masses (i.e. mixtures with fixed number of components).

Authors:Priscilla Ong [aut, edt], Raffaele Argiento [aut], Bruno Bodin [aut, cre], Maria De Iorio [aut]

AntMAN_1.1.0.tar.gz
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AntMAN.pdf |AntMAN.html✨
AntMAN/json (API)

# Install 'AntMAN' in R:
install.packages('AntMAN', repos = c('https://bbodin.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/bbodin/antman/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

    On CRAN:

    59 exports 2 stars 1.03 score 75 dependencies 4 scripts 361 downloads

    Last updated 3 years agofrom:b1aed991b8. Checks:OK: 1 ERROR: 8. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKSep 07 2024
    R-4.5-win-x86_64ERRORSep 07 2024
    R-4.5-linux-x86_64ERRORSep 07 2024
    R-4.4-win-x86_64ERRORSep 07 2024
    R-4.4-mac-x86_64ERRORSep 07 2024
    R-4.4-mac-aarch64ERRORSep 07 2024
    R-4.3-win-x86_64ERRORSep 07 2024
    R-4.3-mac-x86_64ERRORSep 07 2024
    R-4.3-mac-aarch64ERRORSep 07 2024

    Exports:AM_clusteringAM_coclusteringAM_demo_mvb_poiAM_demo_mvn_poiAM_demo_uvn_poiAM_demo_uvp_poiAM_emp_bayes_uninormAM_extractAM_find_gamma_DeltaAM_find_gamma_NegBinAM_find_gamma_PoisAM_mcmc_fitAM_mcmc_parametersAM_mcmc_refitAM_mix_components_prior_diracAM_mix_components_prior_negbinAM_mix_components_prior_poisAM_mix_hyperparams_multiberAM_mix_hyperparams_multinormAM_mix_hyperparams_uninormAM_mix_hyperparams_unipoisAM_mix_weights_prior_gammaAM_plot_chaincorAM_plot_densityAM_plot_mvb_cluster_frequencyAM_plot_pairsAM_plot_pmfAM_plot_similarity_matrixAM_plot_tracesAM_plot_valuesAM_prior_K_DeltaAM_prior_K_NegBinAM_prior_K_PoisAM_reshapeAM_salsoAM_sample_multibinAM_sample_multinormAM_sample_uninormAM_sample_unipoisdensity_discrete_variablesextract_targetgenerate_column_namesIAM_compute_stirling_ricor_absIAM_compute_stirling_ricor_logIAM_mcmc_errorIAM_mcmc_neffIAM_VnkDeltaIAM_VnkNegBinIAM_VnkPoissonlist_valuesplot.AM_mcmc_outputplot.AM_priorsummary.AM_mcmc_configurationsummary.AM_mcmc_outputsummary.AM_mix_components_priorsummary.AM_mix_hyperparamssummary.AM_mix_weights_priorsummary.AM_priorunivariate_plot

    Dependencies:abindbackportsbayesplotbitbit64broombroom.helperscardscheckmateclicliprcolorspacecpp11crayondistributionaldplyrfansifarverforcatsgenericsGGallyggplot2ggridgesggstatsgluegtablehavenhmsisobandlabelinglabelledlatticelifecyclelpSolvemagrittrMASSMatrixmatrixStatsmcclustmgcvmunsellmvtnormnlmenumDerivpatchworkpillarpkgconfigplyrposteriorprettyunitsprogresspurrrR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackreadrreshape2rlangsalsoscalesstringistringrtensorAtibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithr