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).
| Version: | 1.4.3 |
| Depends: | R (≥ 1.8.0), cluster |
| Author: | Katherine S. Pollard, with Mark J. van der Laan. |
| Maintainer: | Katherine S. Pollard <kpollard at wald.ucdavis.edu> |
| License: | GPL version 2 or newer |
| URL: | http://www.r-project.org, http://www.stat.berkeley.edu/~laan/, http://docpollard.com |
| In views: | Cluster, Multivariate |
| CRAN checks: | hopach results |
Downloads:
| Package source: | hopach_1.4.3.tar.gz |
| MacOS X binary: | hopach_1.4.3.tgz |
| Windows binary: | hopach_1.4.3.zip |
| Reference manual: | hopach.pdf |
| Old sources: | hopach archive |