baybi: Bayesian Biclustering with Subject and Variable Importance

The package builds a dendrogram for subjects and variables with log posterior of a simple linear model. After data are grouped the Bayes Factor of a mixture versus a single component is given as an importance measure. Model hyperparameters are needed to be given or estimated from data to apply the algorithm.

AuthorVahid PARTOVI NIA
Date of publication2014-11-24 23:57:13
MaintainerVahid PARTOVI NIA <partovi@math.mcgill.ca>
LicenseGPL (>= 2)
Version1.0

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Files

DESCRIPTION
NAMESPACE
R
R/baybiclust.R R/zzz.R
data
data/julien.rda
man
man/baybiclust.Rd man/baybiplot.Rd
src
src/Makevars
src/cbaybi.c

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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