Package:	clusterGeneration
Version:	1.2.4
Date:		2007-10-30
Title:		random cluster generation (with specified degree of separation)
Author:		Weiliang Qiu <stwxq@channing.harvard.edu>,
Harry Joe <harry@stat.ubc.ca>.
Maintainer:	Weiliang Qiu<stwxq@channing.harvard.edu>
Depends:	R (>= 2.0.0), MASS
Description:	The package contains functions for generating random
clusters, generating random covariance/correlation matrices,
calculating a separation index (data and population version)
for pairs of clusters or cluster distributions, and
1-D and 2-D projection plots to visualize clusters.
The package also contains a function to generate random
clusters based on factorial designs with factors such as
degree of separation, number of clusters,
number of variables, number of noisy variables.
License:	GPL version 2 or newer
Packaged: Tue Oct 30 15:25:42 2007; stwxq

Package: clusterGeneration
Version: 1.2.7
Date: 2009-02-04
Title: random cluster generation (with specified degree of separation)
Author: Weiliang Qiu <stwxq@channing.harvard.edu>, Harry Joe
<harry@stat.ubc.ca>.
Maintainer: Weiliang Qiu<stwxq@channing.harvard.edu>
Depends: R (>= 2.8.1), MASS
Description: The package contains functions for generating random
clusters, generating random covariance/correlation matrices,
calculating a separation index (data and population version)
for pairs of clusters or cluster distributions, and 1-D and 2-D
projection plots to visualize clusters.  The package also
contains a function to generate random clusters based on
factorial designs with factors such as degree of separation,
number of clusters, number of variables, number of noisy
variables.
License: GPL (>= 2)
Packaged: Wed Feb 4 16:01:43 2009; stwxq
Repository: CRAN
Date/Publication: 2009-02-04 20:59:31

Title: Random Cluster Generation (with Specified Degree of Separation)
Description: We developed the clusterGeneration package to provide functions
for generating random clusters, generating random

Title: Identifying clusters in genomics data by recursive partitioning
Author: Gro Nilsen and Ole Christian Lingjaerde
Description: The Partitioning Algorithm based on Recursive Thresholding
(PART) is used to recursively uncover clusters and subclusters
in the data. Functionality is also available for visualization