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 |