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bclust (version 1.3)

Bayesian clustering using spike-and-slab hierarchical model, suitable for clustering high-dimensional data.

Description

The package builds a dendrogram with log posterior as a natural distance defined by the model. It is also capable to computing Bayesian discrimination probabilities equivalent to the implemented Bayesian clustering. Spike-and-Slab models are adopted in a way to be able to produce an importance measure for clustering and discriminant variables. The method works properly for data with small sample size and high dimensions. The model parameter estimation maybe difficult, depending on data structure and the chosen distribution family.

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Version

Install

install.packages('bclust')

Monthly Downloads

18

Version

1.3

License

GPL (>= 2)

Maintainer

Vahid NIA

Last Published

April 17th, 2012

Functions in bclust (1.3)

loglikelihood

computes the model log likelihood useful for estimation of the transformed.par
teethplot

produces teeth plot useful for demonstating a grouping on clustered subjects
viplot

variable importance plot
bclust

Bayesian agglomerative clustering for high dimensional data with variable selection.
gaelle

Messerli et. al. metabolomic data
profileplot

a plot useful to visualise replicated data
meancss

computes statistics necessary for the evaluation of the log likelihood
ditplot

dendrogram-image-teeth plot
bclustvs

bclustvs (Bayesian CLUSTering with Variable Selection) is a class
bdiscrim

discrimination using a Bayesian linear model
imp

calculates variable and variable-cluster importances
dptplot

dendrogram-profile-teeth plot