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Authors: Vahid Partovi Nia, Anthony C. Davison
Title: [download]
(2296)
High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust
Reference: Vol. 47, Issue 5, Apr 2012
Submitted 2010-01-15, Accepted 2012-04-05
Type: Article
Abstract:

The R package bclust is useful for clustering high-dimensional continuous data. The package uses a parametric spike-and-slab Bayesian model to downweight the effect of noise variables and to quantify the importance of each variable in agglomerative clustering. We take advantage of the existence of closed-form marginal distributions to estimate the model hyper-parameters using empirical Bayes, thereby yielding a fully automatic method. We discuss computational problems arising in implementation of the procedure and illustrate the usefulness of the package through examples.

Paper: [download]
(2296)
High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust
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Supplements: [download]
(438)
bclust_1.3.tar.gz: R source package
(application/x-gzip, 48.4 KB)
[download]
(441)
v47i05.R: R example code from the paper
(application/octet-stream, 4.5 KB)
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(445)
simG.RData: Simulated Gaussian data in R binary format
(application/octet-stream, 15.2 KB)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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