AM_clustering | Return the clustering matrix |

AM_coclustering | Return the co-clustering matrix |

AM_demo_mvb_poi | Returns an example of 'AM_mcmc_fit' output produced by the multivariate bernoulli model |

AM_demo_mvn_poi | Returns an example of 'AM_mcmc_fit' output produced by the multivariate gaussian model |

AM_demo_uvn_poi | Returns an example of 'AM_mcmc_fit' output produced by the univariate Gaussian model |

AM_demo_uvp_poi | Returns an example of 'AM_mcmc_fit' output produced by the univariate Poisson model |

AM_emp_bayes_uninorm | compute the hyperparameters of an Normal-Inverse-Gamma distribution using an empirical Bayes approach |

AM_extract | Extract values within a 'AM_mcmc_output' object |

AM_find_gamma_Delta | Given that the prior on M is a dirac delta, find the gamma hyperparameter of the weights prior to match E(K)=K*, where K* is user-specified |

AM_find_gamma_NegBin | Given that the prior on M is a Negative Binomial, find the gamma hyperparameter of the weights prior to match E(K)=K*, where K* is user-specified |

AM_find_gamma_Pois | Given that the prior on M is a shifted Poisson, find the gamma hyperparameter of the weights prior to match E(K)=K^{*}, where K^{*} is user-specified |

AM_mcmc_configuration | S3 class AM_mcmc_configuration |

AM_mcmc_fit | Performs a Gibbs sampling |

AM_mcmc_output | S3 class AM_mcmc_output |

AM_mcmc_parameters | MCMC Parameters |

AM_mcmc_refit | Performs a Gibbs sampling reusing previous configuration |

AM_mix_components_prior | S3 class AM_mix_components_prior |

AM_mix_components_prior_dirac | Generate a configuration object that contains a Point mass prior |

AM_mix_components_prior_negbin | Generate a configuration object for a Shifted Negative Binomial prior on the number of mixture components |

AM_mix_components_prior_pois | Generate a configuration object for a Poisson prior on the number of mixture components |

AM_mix_hyperparams | S3 class AM_mix_hyperparams |

AM_mix_hyperparams_multiber | multivariate Bernoulli mixture hyperparameters (Latent Class Analysis) |

AM_mix_hyperparams_multinorm | multivariate Normal mixture hyperparameters |

AM_mix_hyperparams_uninorm | univariate Normal mixture hyperparameters |

AM_mix_hyperparams_unipois | univariate Poisson mixture hyperparameters |

AM_mix_weights_prior | S3 class AM_mix_weights_prior |

AM_mix_weights_prior_gamma | specify a prior on the hyperparameter gamma for the Dirichlet mixture weights prior |

AM_plot_chaincor | Plot the Autocorrelation function |

AM_plot_density | Plot the density of variables from 'AM_mcmc_output' object |

AM_plot_mvb_cluster_frequency | Visualise the cluster frequency plot for the multivariate bernoulli model |

AM_plot_pairs | Plot 'AM_mcmc_output' scatterplot matrix |

AM_plot_pmf | Plot the probability mass function of variables from 'AM_mcmc_output' object |

AM_plot_similarity_matrix | Plot the Similarity Matrix |

AM_plot_traces | Plot traces of variables from an 'AM_mcmc_output' object |

AM_plot_values | Plot posterior interval estimates obtained from MCMC draws |

AM_prior | S3 class AM_prior |

AM_prior_K_Delta | Computes the prior on the number of clusters |

AM_prior_K_NegBin | computes the prior number of clusters |

AM_prior_K_Pois | Computes the prior number of clusters |

AM_salso | Sequentially Allocated Latent Structure Optimisation |

AntMAN | AntMAN: A package for fitting finite Bayesian Mixture models with a random number of components |

brain | Teen Brain Images from the National Institutes of Health, U.S. |

carcinoma | Carcinoma dataset |

galaxy | Galaxy velocities dataset |

plot.AM_mcmc_output | plot AM_mcmc_output |

plot.AM_prior | plot AM_prior |

said | Usage frequency of the word "said" in the Brown corpus |

summary.AM_mcmc_configuration | summary information of the AM_mcmc_configuration object |

summary.AM_mcmc_output | summary information of the AM_mcmc_output object |

summary.AM_mix_components_prior | summary information of the AM_mix_components_prior object |

summary.AM_mix_hyperparams | summary information of the AM_mix_hyperparams object |

summary.AM_mix_weights_prior | summary information of the AM_mix_weights_prior object |

summary.AM_prior | summary information of the AM_prior object |