Algorithm to process hierarchical clustering on individuals (from a matrix individuals x variables). The dissimilarity used in the observation space is the loglikelihood ratio, i.e. D(i,j) = log f(Y_i) + log f(Y_j)  log f(Y_i U Y_j) where Y_i is the vector of observations from individual i. The statistical model defining the considered likelihood is standard Gaussian or ZeroInflated Gaussian (i.e. a GaussianBernoulli mixture). The agglomeration method is also the loglikelihood ratio, however between clusters in this case.
Package details 


Author  Ghislain Durif <[email protected]>, Franck Picard <[email protected]> 
Date of publication  20160503 09:28:51 
Maintainer  Ghislain Durif <[email protected]> 
License  GPL (>= 2) 
Version  0.2 
Package repository  View on RForge 
Installation 
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