Algorithm to process hierarchical clustering on individuals (from a matrix individuals x variables). The dissimilarity used in the observation space is the log-likelihood 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 Zero-Inflated Gaussian (i.e. a Gaussian-Bernoulli mixture). The agglomeration method is also the log-likelihood ratio, however between clusters in this case.
Package details |
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Author | Ghislain Durif <ghislain.durif@univ-lyon1.fr>, Franck Picard <franck.picard@univ-lyon1.fr> |
Maintainer | Ghislain Durif <ghislain.durif@univ-lyon1.fr> |
License | GPL (>= 2) |
Version | 0.2 |
Package repository | View on R-Forge |
Installation |
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