A Modular, Integrated Approach to Maximum Entropy Distribution Modeling R package MIAmaxent version 1.4.1 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>). Software 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 Julien Vollering <julienvollering@gmail.com> Comprehensive R Archive Network (CRAN) Julien Vollering [aut, cre], Sabrina Mazzoni [aut], Rune Halvorsen [aut], Steven Phillips [cph], Michael Bedward [ctb] MIT + file LICENSE (https://CRAN.R-project.org/package=MIAmaxent/LICENSE) 2025-12-09 application/tgz https://CRAN.R-project.org/package=MIAmaxent doi:10.32614/CRAN.package.MIAmaxent