Gets a point estimate of the partition using posterior expected adjusted Rand index (PEAR)

Gets a point estimate of the partition using posterior expected adjusted Rand index (PEAR)

Usage

cluster_est_pear(c)

Arguments

c

a list of vector of length n. c[[j]][i] is the cluster allocation of observation i=1...n at iteration j=1...N.

Value

a list:

c_est:

a vector of length n. Point estimate of the partition

pear:

a vector of length N. pear[j] is the posterior expected adjusted Rand index associated to partition c[[j]]

similarity:

matrix of size n x n. Similarity matrix (see similarityMat)

opt_ind:

the index of the optimal partition among the MCMC iterations.

References

A. Fritsch, K. Ickstadt. Improved Criteria for Clustering Based on the Posterior Similarity Matrix, in Bayesian Analysis, Vol.4 : p.367-392 (2009)

See also

similarityMat similarityMatC

Author

Chariff Alkhassim