enmpa: enmpa: Ecological Niche Modeling using Presence-Absence Data

In enmpa: Ecological Niche Modeling using Presence-Absence Data

enmpa: Ecological Niche Modeling using Presence-Absence Data

Description

enmpa contains a set of tools to perform detailed Ecological Niche Modeling using presence-absence data.

Details

It includes algorithms for data partitioning, model fitting, calibration, evaluation, selection, and prediction. Other functions help to explore model features as such variable response curves and variable importance.

Main functions in enmpa

calibration_glm, evaluation_stats, fit_glms, fit_selected, get_formulas, independent_eval1, kfold_partition, model_selection model_validation, niche_signal, optimize_metrics, predict_glm, predict_selected, response_curve, resp2var, var_importance, jackknife, plot_jk

Author(s)

Maintainer: Luis F. Arias-Giraldo [e-mail] (ORCID)

Authors:

• Marlon E. Cobos [e-mail] (ORCID)

Other contributors:

• A. Townsend Peterson [e-mail] (ORCID) [contributor]

See Also

Useful links:

• https://github.com/Luisagi/enmpa

• Report bugs at https://github.com/Luisagi/enmpa/issues

enmpa documentation built on June 13, 2025, 1:10 a.m.