The moving party shall advise the Court in its application whether opposing counsel will be filing opposition and explain what efforts, if any, have been made to confer with opposing counsel regarding the substance of the application and any potential resolution prior to the filing of the application. The moving party shall immediately serve the ex parte application on the opposing party by fax, email, or hand delivery and shall notify the opposing party that any opposition must be filed not later than 24 hours after the service of the application. If a hearing is necessary, the court clerk will notify counsel of the date and time of the hearing. Counsel will be notified of the Court’s ruling. Ex parte applications are taken under submission on the papers and are rarely set for hearing. Ex Parte Applications: Ex parte applications are solely for extraordinary relief and should be used with discretion. # AntMAN Package #' Sequentially Allocated Latent Structure Optimisation #' #' Heuristic partitioning to minimise the expected Binder loss function #' with respect to a given expected adjacency matrix.6. IAM_compute_stirling_ricor_log: Compute stirling ricor log.IAM_compute_stirling_ricor_abs: Compute the logarithm of the absolute value of the.brain: Teen Brain Images from the National Institutes of Health.AntMAN: AntMAN: A package for fitting finite Bayesian Mixture models.AM_sample_multinorm: AM_sample_multinorm.AM_salso: Sequentially Allocated Latent Structure Optimisation.AM_prior_K_Pois: Computes the prior number of clusters.AM_prior_K_NegBin: computes the prior number of clusters.AM_prior_K_Delta: Computes the prior on the number of clusters.AM_plot_values: Plot posterior interval estimates obtained from MCMC draws.AM_plot_traces: Plot traces of variables from an 'AM_mcmc_output' object.AM_plot_similarity_matrix: Plot the Similarity Matrix.AM_plot_pmf: Plot the probability mass function of variables from.AM_plot_pairs: Plot 'AM_mcmc_output' scatterplot matrix.AM_plot_mvb_cluster_frequency: Visualise the cluster frequency plot for the multivariate.AM_plot_density: Plot the density of variables from 'AM_mcmc_output' object.AM_plot_chaincor: Plot the Autocorrelation function.AM_mix_weights_prior_gamma: specify a prior on the hyperparameter gamma for the Dirichlet.AM_mix_weights_prior: S3 class AM_mix_weights_prior.AM_mix_hyperparams_unipois: univariate Poisson mixture hyperparameters.AM_mix_hyperparams_uninorm: univariate Normal mixture hyperparameters.AM_mix_hyperparams_multinorm: multivariate Normal mixture hyperparameters.AM_mix_hyperparams_multiber: multivariate Bernoulli mixture hyperparameters (Latent Class.AM_mix_hyperparams: S3 class AM_mix_hyperparams.AM_mix_components_prior_pois: Generate a configuration object for a Poisson prior on the.AM_mix_components_prior_negbin: Generate a configuration object for a Shifted Negative.AM_mix_components_prior_dirac: Generate a configuration object that contains a Point mass.AM_mix_components_prior: S3 class AM_mix_components_prior.AM_mcmc_refit: Performs a Gibbs sampling reusing previous configuration.AM_mcmc_output: S3 class AM_mcmc_output.AM_mcmc_configuration: S3 class AM_mcmc_configuration.AM_find_gamma_Pois: Given that the prior on M is a shifted Poisson, find the.AM_find_gamma_NegBin: Given that the prior on M is a Negative Binomial, find the.AM_find_gamma_Delta: Given that the prior on M is a dirac delta, find the gamma.AM_extract: Extract values within a 'AM_mcmc_output' object.AM_emp_bayes_uninorm: compute the hyperparameters of an Normal-Inverse-Gamma.AM_demo_uvp_poi: Returns an example of 'AM_mcmc_fit' output produced by the.AM_demo_uvn_poi: Returns an example of 'AM_mcmc_fit' output produced by the.AM_demo_mvn_poi: Returns an example of 'AM_mcmc_fit' output produced by the.AM_demo_mvb_poi: Returns an example of 'AM_mcmc_fit' output produced by the.AM_coclustering: Return the co-clustering matrix.AM_clustering: Return the clustering matrix.

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