opticut: Likelihood Based Optimal Partitioning and Indicator Species Analysis

Likelihood based optimal partitioning and indicator species analysis. Finding the best binary partition for each species based on model selection, with the possibility to take into account modifying/confounding variables as described in Kemencei et al. (2014) <doi:10.1556/ComEc.15.2014.2.6>. The package implements binary and multi-level response models, various measures of uncertainty, Lorenz-curve based thresholding, with native support for parallel computations.

Version: 0.1-2
Depends: R (≥ 3.1.0), pbapply (≥ 1.3-0)
Imports: MASS, pscl, betareg, ResourceSelection (≥ 0.3-2), parallel, mefa4
Published: 2018-02-01
Author: Peter Solymos [cre, aut], Ermias T. Azeria [ctb]
Maintainer: Peter Solymos <solymos at ualberta.ca>
BugReports: https://github.com/psolymos/opticut/issues
License: GPL-2
URL: https://github.com/psolymos/opticut
NeedsCompilation: no
CRAN checks: opticut results

Downloads:

Reference manual: opticut.pdf
Package source: opticut_0.1-2.tar.gz
Windows binaries: r-devel: opticut_0.1-2.zip, r-release: opticut_0.1-2.zip, r-oldrel: opticut_0.1-2.zip
OS X binaries: r-release: opticut_0.1-2.tgz, r-oldrel: not available
Old sources: opticut archive

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