ziLRhClust: Hierarchical Clustering Based on Log-Likelihood Ratio for Zero-Inflated Data

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.

AuthorGhislain Durif <ghislain.durif@univ-lyon1.fr>, Franck Picard <franck.picard@univ-lyon1.fr>
Date of publication2016-05-03 09:28:51
MaintainerGhislain Durif <ghislain.durif@univ-lyon1.fr>
LicenseGPL (>= 2)
Version0.2

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Files

DESCRIPTION
LICENCE.note
NAMESPACE
R
R/RcppExports.R R/hClust_llr.R R/plot_heatmap.R
build
build/partial.rdb
inst
inst/include
inst/include/ziLRhClust.h
man
man/hClust_llr.Rd man/plot_heatmap.Rd man/ziLRhClust-package.Rd
src
src/RcppExports.cpp
src/hclust.cpp
src/hclust.h
src/hclustOriginal.cpp
src/hclustOriginal.h
src/hclustZI.cpp
src/hclustZI.h
src/hclust_wrapper.cpp
src/order.cpp
src/order.h

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