glm_mx: Maxent-like Generalized Linear Models (GLM)

In kuenm2: Detailed Development of Ecological Niche Models

Maxent-like Generalized Linear Models (GLM)

Description

This function fits a Generalized Linear Model (GLM) to binary presence-background data. It allows for the specification of custom weights, with a default in which presences have a weight of 1 and background 100.

Usage

glm_mx(formula, family = binomial(link = "cloglog"), data,
       weights = NULL, ...)

Arguments

formula	A formula specifying the model to be fitted, in the format used by glm.
family	A description of the error distribution and link function to be used in the model. Defaults to binomial(link = "cloglog"), which is commonly used for presence-background data.
data	A data.frame containing the variables in the model. Must include a column named pr_bg that indicates whether a record is a presence (1) or background (0), and at least another column with an independent variable (predictor).
weights	Optional. A numeric vector of weights for each observation. If not provided, default weights of 1 for presences and 100 for background are used.
...	Additional arguments to be passed to glm.

Details

For more details about glms using presence and background emulating what Maxent does, see Fithian and Hastie (2013) doi:10.1214/13-AOAS667.

Value

A fitted glm object. The model object includes the minimum and maximum values of the non-factor variables in the dataset, stored as model$varmin and model$varmax.

kuenm2 documentation built on April 21, 2026, 1:07 a.m.