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. The package is described in
Vollering et al. (2019; <doi:10.1002/ece3.5654>).
| Version: |
1.3.1 |
| Depends: |
R (≥ 2.10) |
| Imports: |
dplyr (≥ 0.4.3), e1071 (≥ 1.6-7), graphics, terra, rlang, stats, utils |
| Suggests: |
knitr, rmarkdown, R.rsp |
| Published: |
2024-08-23 |
| DOI: |
10.32614/CRAN.package.MIAmaxent |
| Author: |
Julien Vollering [aut, cre],
Sabrina Mazzoni [aut],
Rune Halvorsen [aut],
Steven Phillips [cph],
Michael Bedward [ctb] |
| Maintainer: |
Julien Vollering <julienvollering at gmail.com> |
| BugReports: |
https://github.com/julienvollering/MIAmaxent/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/julienvollering/MIAmaxent |
| NeedsCompilation: |
no |
| Citation: |
MIAmaxent citation info |
| Materials: |
README NEWS |
| CRAN checks: |
MIAmaxent results |
Documentation:
Downloads:
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