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| asCanonical | Coerce a Vector of Cluster Labels to Canonical Form |
| asClusterLabels | Coerce a Set Partition in List Structure to Numeric Vectors of Cluster Label |
| asSetPartition | Coerce a Set Partition as Numeric Vectors of Cluster Labels to a List Structure |
| clusterProportions | Compute the Proportion of Items in Each Cluster for All Partitions |
| clusterTrace | Plot Traces of Cluster Sizes |
| clusterWithItem | Identify Which Cluster Contains a Given Item |
| createNewCluster | Create a New Cluster with Given Item |
| dCRP | Compute Probability Mass of a Partition Under the Two Parameter Chinese Restaurant Process (CRP) |
| getThetas | Get theta Parameters from a Numeric Vector of Cluster Labels and Unique phi Values |
| isCanonical | Check if a Vector of Cluster Labels is in Canonical Form |
| joinExistingCluster | Join Item to an Existing Cluster |
| nClusters | Count the Number of Clusters in a Set Partition |
| nealAlgorithm3 | Conjugate Gibbs Sampler for a Partition |
| p18_bern | Multivariate Independent Bernoulli Data (p = 18) |
| p18_bern_1 | Multivariate Independent Bernoulli Data (p = 18) |
| p18_bern_2 | Multivariate Independent Bernoulli Data (p = 18) |
| p18_bern_3 | Multivariate Independent Bernoulli Data (p = 18) |
| p18_corr_mvn | Correlated Multivariate Normal Data (p = 18) |
| p18_corr_mvn_1 | Correlated Multivariate Normal Data (p = 18) |
| p18_corr_mvn_2 | Correlated Multivariate Normal Data (p = 18) |
| p18_corr_mvn_3 | Correlated Multivariate Normal Data (p = 18) |
| p18_mvn | Independent Multivariate Normal Data (p = 18) |
| p18_mvn_1 | Independent Multivariate Normal Data (p = 18) |
| p18_mvn_2 | Independent Multivariate Normal Data (p = 18) |
| p18_mvn_3 | Independent Multivariate Normal Data (p = 18) |
| p6_bern | Multivariate Independent Bernoulli Data (p = 6) |
| p6_bern_1 | Multivariate Independent Bernoulli Data (p = 6) |
| p6_bern_2 | Multivariate Independent Bernoulli Data (p = 6) |
| p6_bern_3 | Multivariate Independent Bernoulli Data (p = 6) |
| p6_big_bern | Large Sample Multivariate Independent Bernoulli Data (p = 6) |
| p6_big_bern_1 | Large Sample Multivariate Independent Bernoulli Data (p = 6) |
| p6_big_bern_2 | Large Sample Multivariate Independent Bernoulli Data (p = 6) |
| p6_big_bern_3 | Large Sample Multivariate Independent Bernoulli Data (p = 6) |
| p6_mvn | Independent Multivariate Normal Data (p = 6) |
| p6_mvn_1 | Independent Multivariate Normal Data (p = 6) |
| p6_mvn_2 | Independent Multivariate Normal Data (p = 6) |
| p6_mvn_3 | Independent Multivariate Normal Data (p = 6) |
| partitionEntropy | Calculate the Entropy of a Set Partition |
| poch | Compute the Pochhammer Symbol (Rising Factorials) With Increment |
| psm | Compute the Posterior Pairwise Similarity for All Pairs of Items |
| psmMergeSplit | Merge-Split Sampling for a Partition Based on Sequential Allocation Informed by Pairwise Similarities |
| psmMergeSplit_base | Base Functionality for the psmMergeSplit Function |
| restrictedGibbsMergeSplit | Merge-Split Sampling for a Partition Based on Restricted Gibbs Scans |
| seqAllocatedMergeSplit | Merge-split Sampling for a Partition Based on Sequential Allocation of Items |
| seqAllocatedMergeSplit_base | Base Functionality for the seqAllocatedMergeSplit Function |
| simpleMergeSplit | Merge-Split Sampling for a Partition Using Uniformly Random Allocation |
| sizeOfLargestCluster | Calculate the Number of Items in the Largest Cluster of a Set Partition |
| transformedWeights | Enumerate Transformed Weights for Choosing i and j Non-Uniformly |