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
AntMAN_1.1.0.zip(r-4.5)AntMAN_1.1.0.zip(r-4.4)AntMAN_1.1.0.zip(r-4.3)
AntMAN_1.1.0.tgz(r-4.5-x86_64)AntMAN_1.1.0.tgz(r-4.5-arm64)AntMAN_1.1.0.tgz(r-4.4-x86_64)AntMAN_1.1.0.tgz(r-4.4-arm64)AntMAN_1.1.0.tgz(r-4.3-x86_64)AntMAN_1.1.0.tgz(r-4.3-arm64)
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AntMAN_1.1.0.tgz(r-4.4-emscripten)AntMAN_1.1.0.tgz(r-4.3-emscripten)
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'))

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

On CRAN:

Conda-Forge:

openblascppopenmp

3.30 score 2 stars 4 scripts 337 downloads 59 exports 64 dependencies

Last updated 4 years agofrom:b1aed991b8. Checks:1 OK, 11 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-win-x86_64ERRORMar 06 2025
R-4.5-mac-x86_64ERRORMar 06 2025
R-4.5-mac-aarch64ERRORMar 06 2025
R-4.5-linux-x86_64ERRORMar 06 2025
R-4.4-win-x86_64ERRORMar 06 2025
R-4.4-mac-x86_64ERRORMar 06 2025
R-4.4-mac-aarch64ERRORMar 06 2025
R-4.4-linux-x86_64ERRORMar 06 2025
R-4.3-win-x86_64ERRORMar 06 2025
R-4.3-mac-x86_64ERRORMar 06 2025
R-4.3-mac-aarch64ERRORMar 06 2025

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:abindbackportsbayesplotcheckmateclicolorspacecpp11crayondistributionaldplyrfansifarverforcatsgenericsGGallyggplot2ggridgesggstatsgluegtablehmsisobandlabelinglatticelifecyclelpSolvemagrittrMASSMatrixmatrixStatsmcclustmgcvmunsellmvtnormnlmenumDerivpatchworkpillarpkgconfigplyrposteriorprettyunitsprogresspurrrR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackreshape2rlangsalsoscalesstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr