Search Algorithms and Loss Functions for Bayesian Clustering

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Documentation for package ‘salso’ version 0.3.53

• DESCRIPTION file.
• Package NEWS.

Help Pages

ARI	Compute Partition Loss or the Expectation of Partition Loss
bell	Compute the Bell Number
binder	Compute Partition Loss or the Expectation of Partition Loss
canonicalize_cluster_labels	Canonicalize Cluster Labels
chips	CHIPS Partition Greedy Search
dlso	Latent Structure Optimization Based on Draws
enumerate.partitions	Enumerate Partitions of a Set
enumerate.permutations	Enumerate Permutations of Items
ID	Compute Partition Loss or the Expectation of Partition Loss
iris.clusterings	Clusterings of the Iris Data
lbell	Compute the Bell Number
NID	Compute Partition Loss or the Expectation of Partition Loss
NVI	Compute Partition Loss or the Expectation of Partition Loss
omARI	Compute Partition Loss or the Expectation of Partition Loss
omARI.approx	Compute Partition Loss or the Expectation of Partition Loss
partition.loss	Compute Partition Loss or the Expectation of Partition Loss
plot.salso.summary	Heatmap, Multidimensional Scaling, Pairs, and Dendrogram Plotting for Partition Estimation
psm	Compute an Adjacency or Pairwise Similarity Matrix
RI	Compute Partition Loss or the Expectation of Partition Loss
salso	SALSO Greedy Search
summary.salso.estimate	Summary of Partitions Estimated Using Posterior Expected Loss
threshold	Threshold CHIPS Output
VI	Compute Partition Loss or the Expectation of Partition Loss
VI.lb	Compute Partition Loss or the Expectation of Partition Loss