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:	0.2.0
Depends:	R (≥ 3.1.0)
Imports:	stats, methods, mvabund (≥ 3.1), ordinal (≥ 2015.1-21)
Suggests:	testthat, knitr, rmarkdown
Published:	2018-01-16
DOI:	10.32614/CRAN.package.optimus
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

Documentation:

Reference manual:	optimus.pdf
Vignettes:	Optimus workflow

Downloads:

Package source:	optimus_0.2.0.tar.gz
Windows binaries:	r-devel: optimus_0.2.0.zip, r-release: optimus_0.2.0.zip, r-oldrel: optimus_0.2.0.zip
macOS binaries:	r-release (arm64): optimus_0.2.0.tgz, r-oldrel (arm64): optimus_0.2.0.tgz, r-release (x86_64): optimus_0.2.0.tgz, r-oldrel (x86_64): optimus_0.2.0.tgz
Old sources:	optimus archive

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