Package: hopach
Version: 1.1.1
Title: Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)
Author: Katherine S. Pollard <kpollard@soe.ucsc.edu>, with
Mark J. van der Laan <laan@stat.berkeley.edu>.
Maintainer: Katherine S. Pollard <kpollard@soe.ucsc.edu>
Depends: R (>= 1.8.0), cluster
Description: The HOPACH clustering algorithm builds a hierarchical tree
of clusters by recursively partitioning a data set, while ordering
and possibly collapsing clusters at each level. The algorithm uses
the Mean/Median Split Silhouette (MSS) criteria to identify the
level of the tree with maximally homogeneous clusters. It also runs
the tree down to produce a final ordered list of the elements. The
non-parametric bootstrap allows one to estimate the probability that
each element belongs to each cluster (fuzzy clustering).
License: GPL version 2 or newer
URL: http://www.r-project.org,
http://www.stat.berkeley.edu/~laan/,
http://lowelab.ucsc.edu/katie/
Packaged: Tue Apr 19 10:22:05 2005; kpollard

Package: hopach
Version: 1.2.1
Title: Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)
Author: Katherine S. Pollard <kpollard@soe.ucsc.edu>, with
Mark J. van der Laan <laan@stat.berkeley.edu>.
Maintainer: Katherine S. Pollard <kpollard@soe.ucsc.edu>
Depends: R (>= 1.8.0), cluster
Description: The HOPACH clustering algorithm builds a hierarchical tree
of clusters by recursively partitioning a data set, while ordering
and possibly collapsing clusters at each level. The algorithm uses
the Mean/Median Split Silhouette (MSS) criteria to identify the
level of the tree with maximally homogeneous clusters. It also runs
the tree down to produce a final ordered list of the elements. The
non-parametric bootstrap allows one to estimate the probability that
each element belongs to each cluster (fuzzy clustering).
License: GPL version 2 or newer
URL: http://www.r-project.org,
http://www.stat.berkeley.edu/~laan/,
http://lowelab.ucsc.edu/katie/
Packaged: Tue Jul  5 12:44:30 2005; kpollard

Package: hopach
Version: 1.4.0
Title: Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)
Author: Katherine S. Pollard <kpollard@soe.ucsc.edu>, with
Mark J. van der Laan <laan@stat.berkeley.edu>.
Maintainer: Katherine S. Pollard <kpollard@soe.ucsc.edu>
Depends: R (>= 1.8.0), cluster
Description: The HOPACH clustering algorithm builds a hierarchical tree
of clusters by recursively partitioning a data set, while ordering
and possibly collapsing clusters at each level. The algorithm uses
the Mean/Median Split Silhouette (MSS) criteria to identify the
level of the tree with maximally homogeneous clusters. It also runs
the tree down to produce a final ordered list of the elements. The
non-parametric bootstrap allows one to estimate the probability that
each element belongs to each cluster (fuzzy clustering).
License: GPL version 2 or newer
URL: http://www.r-project.org,
http://www.stat.berkeley.edu/~laan/,
http://lowelab.ucsc.edu/katie/
Packaged: Tue Nov  1 13:26:26 2005; kpollard