R: Merge-Split Samplers for Conjugate Bayesian Nonparametric Models

# Merge-Split Samplers for Conjugate Bayesian Nonparametric Models

## Documentation for package ‘sams’ version 0.4.3

- DESCRIPTION file
- Package NEWS

## Help Pages

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