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.
Package details |
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Author | Peter Solymos [cre, aut], Ermias T. Azeria [ctb] |
Maintainer | Peter Solymos <solymos@ualberta.ca> |
License | GPL-2 |
Version | 0.1-2 |
URL | https://github.com/psolymos/opticut |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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