Special functions that enhance other mixed effect model packages by creating overlayed, reduced rank, and reduced model matrices together with multiple data sets to practice the use of these models. For more details see Covarrubias-Pazaran (2016) <doi:10.1371/journal.pone.0156744>.

Runs ecological niche models over all combinations of user-defined settings (i.e., tuning), performs cross validation to evaluate models, and returns data tables to aid in selection of optimal model settings that balance goodness-of-fit and model complexity. Also has functions to partition data spatially (or not) for cross validation, to plot multiple visualizations of results, to run null models to estimate significance and effect sizes of performance metrics, and to calculate range overlap between model predictions, among others. The package was originally built for Maxent models (Phillips et al. 2006, Phillips et al. 2017), but the current version allows possible extensions for any modeling algorithm. The extensive vignette, which guides users through most package functionality but unfortunately has a file size too big for CRAN, can be found here on the package's Github Pages website: <https://jamiemkass.github.io/ENMeval/articles/ENMeval-2.0-vignette.html>.

A set of tools to perform Ecological Niche Modeling with
    presence-absence data. It includes algorithms for data partitioning, 
    model fitting, calibration, evaluation, selection, and prediction. 
    Other functions help to explore signals of ecological niche using univariate
    and multivariate analyses, and model features such as variable response 
    curves and variable importance. Unique characteristics of this package are
    the ability to exclude models with concave quadratic responses, and the
    option to clamp model predictions to specific variables. These tools are
    implemented following principles proposed in
    Cobos et al., (2022) <doi:10.17161/bi.v17i.15985>, 
    Cobos et al., (2019) <doi:10.7717/peerj.6281>, 
    and Peterson et al., (2008) <doi:10.1016/j.ecolmodel.2007.11.008>.