Nothing
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 |
|
---|---|
Author | Peter Solymos [cre, aut] (<https://orcid.org/0000-0001-7337-1740>), Ermias T. Azeria [ctb] |
Maintainer | Peter Solymos <psolymos@gmail.com> |
License | GPL-2 |
Version | 0.1-3 |
URL | https://github.com/psolymos/opticut |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.