opticut: Likelihood Based Optimal Partitioning for Indicator Species Analysis

Likelihood based optimal partitioning for indicator species analysis. Finding the best binary partition for each species based on model selection, possibly controlling for modifying/confounding variables as described in Kemencei et al. (2014) <doi:10.1556/ComEc.15.2014.2.6>. The package also implements various measures of uncertainty based on binary partitions, optimal multinomial partitioning, and exploratory suitability indices, with native support for parallel computations.

Version: 0.1-0
Depends: R (≥ 3.1.0), pbapply (≥ 1.3-0)
Imports: MASS, pscl, betareg, ResourceSelection (≥ 0.3-0), parallel, mefa4
Published: 2016-12-17
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

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Reference manual: opticut.pdf
Package source: opticut_0.1-0.tar.gz
Windows binaries: r-devel: opticut_0.1-0.zip, r-release: opticut_0.1-0.zip, r-oldrel: opticut_0.1-0.zip
OS X Mavericks binaries: r-release: opticut_0.1-0.tgz, r-oldrel: opticut_0.1-0.tgz

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