MIAmaxent: A Modular, Integrated Approach to Maximum Entropy Distribution Modeling

Tools for training, selecting, and evaluating maximum entropy (and standard logistic regression) distribution models. This package provides tools for user-controlled transformation of explanatory variables, selection of variables by nested model comparison, and flexible model evaluation and projection. It follows principles based on the maximum- likelihood interpretation of maximum entropy modeling, and uses infinitely- weighted logistic regression for model fitting.

Version: 1.1.0
Depends: R (≥ 2.10)
Imports: dplyr (≥ 0.4.3), e1071 (≥ 1.6-7), graphics, raster (≥ 2.5-8), stats, utils
Suggests: knitr, rmarkdown, R.rsp
Published: 2019-05-30
Author: Julien Vollering [aut, cre], Sabrina Mazzoni [aut], Rune Halvorsen [aut], Steven Phillips [cph]
Maintainer: Julien Vollering <julien.vollering at hvl.no>
BugReports: https://github.com/julienvollering/MIAmaxent/issues
License: MIT + file LICENSE
URL: https://github.com/julienvollering/MIAmaxent
NeedsCompilation: no
Materials: README NEWS
CRAN checks: MIAmaxent results


Reference manual: MIAmaxent.pdf
Vignettes: A modeling example
Package source: MIAmaxent_1.1.0.tar.gz
Windows binaries: r-devel: MIAmaxent_1.1.0.zip, r-devel-gcc8: MIAmaxent_1.1.0.zip, r-release: MIAmaxent_1.1.0.zip, r-oldrel: MIAmaxent_1.1.0.zip
OS X binaries: r-release: MIAmaxent_1.1.0.tgz, r-oldrel: MIAmaxent_1.1.0.tgz
Old sources: MIAmaxent archive


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