MIAmaxent: A Modular, Integrated Approach to Maximum Entropy Distribution Modeling (original) (raw)
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: | 1.4.0 |
|---|---|
| Depends: | R (≥ 2.10) |
| Imports: | dplyr (≥ 0.4.3), e1071 (≥ 1.6-7), graphics, terra, rlang, stats, utils |
| Suggests: | knitr, rmarkdown, purrr, tidyr, tibble, ggplot2, sf, disdat |
| Published: | 2025-10-18 |
| 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 |
| BugReports: | https://github.com/julienvollering/MIAmaxent/issues |
| License: | MIT + file |
| URL: | https://github.com/julienvollering/MIAmaxent |
| NeedsCompilation: | no |
| Citation: | MIAmaxent citation info |
| Materials: | README, NEWS |
| CRAN checks: | MIAmaxent results [issues need fixing before 2025-12-15] |
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