View source: R/cluster_est_Mbinder_norm.R
cluster_est_Mbinder_norm | R Documentation |
Get a point estimate of the partition using a modified Binder loss function for Gaussian components
cluster_est_Mbinder_norm(c, Mu, Sigma, lambda = 0, a = 1, b = a, logposterior)
c |
a list of vector of length |
Mu |
is a list of length |
Sigma |
is list of length |
lambda |
is a nonnegative tunning parameter allowing further control over the distance function. Default is 0. |
a |
nonnegative constant seen as the unit cost for pairwise misclassification. Default is 1. |
b |
nonnegative constant seen as the unit cost for the other kind of pairwise misclassification. Default is 1. |
logposterior |
vector of logposterior corresponding to each
partition from |
Note that he current implementation only allows Gaussian components.
The modified Binder loss function takes into account the distance between mixture components using #'the Bhattacharyya distance.
a list
:
c_est : |
a vector of length |
cost : |
a vector of length |
similarity : |
matrix of size |
opt_ind : |
the index of the optimal partition among the MCMC iterations. |
Chariff Alkhassim
JW Lau, PJ Green, Bayesian Model-Based Clustering Procedures, Journal of Computational and Graphical Statistics, 16(3):526-558, 2007.
DA Binder, Bayesian cluster analysis, Biometrika 65(1):31-38, 1978.
similarityMat
similarityMatC
similarityMat_nocostC
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