optimus: Model Based Diagnostics for Multivariate Cluster Analysis

Assessment and diagnostics for comparing competing clustering solutions, using predictive models. The main intended use is for comparing clustering/classification solutions of ecological data (e.g. presence/absence, counts, ordinal scores) to 1) find an optimal partitioning solution, 2) identify characteristic species and 3) refine a classification by merging clusters that increase predictive performance. However, in a more general sense, this package can do the above for any set of clustering solutions for i observations of j variables.

Version: 0.1.0
Depends: R (≥ 3.1.0)
Imports: stats, methods, mvabund (≥ 3.1), ordinal (≥ 2015.1-21)
Suggests: testthat, knitr, rmarkdown
Published: 2017-03-24
Author: Mitchell Lyons [aut, cre]
Maintainer: Mitchell Lyons <mitchell.lyons at gmail.com>
BugReports: https://github.com/mitchest/optimus/issues
License: GPL-3
URL: https://github.com/mitchest/optimus/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: optimus results


Reference manual: optimus.pdf
Vignettes: Optimus workflow
Package source: optimus_0.1.0.tar.gz
Windows binaries: r-devel: optimus_0.1.0.zip, r-release: optimus_0.1.0.zip, r-oldrel: optimus_0.1.0.zip
OS X El Capitan binaries: r-release: optimus_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: optimus_0.1.0.tgz


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