bivariate_response: Bivariate response plot for fitted models

In kuenm2: Detailed Development of Ecological Niche Models

Bivariate response plot for fitted models

Description

A plot of suitability prediction in a two-dimensional environmental space.

Usage

bivariate_response(models, variable1 , variable2, modelID = NULL, n = 500,
                   new_data = NULL, extrapolate = TRUE, add_bar = TRUE ,
                   add_limits = TRUE, color_palette	= NULL,
                   xlab = NULL, ylab = NULL, ...)

Arguments

models	an object of class fitted_models returned by the fit_selected() function.
variable1	(character) name of the variable to be plotted in x axis.
variable2	(character) name of the variable to be plotted in y axis.
modelID	(character) name of the ModelID presents in the fitted object. Default = NULL.
n	(numeric) the number of breaks for plotting grid. Default = 500
new_data	a SpatRaster, data.frame, or matrix of variables representing an area of interest. Default = NULL.
extrapolate	(logical) whether to allow extrapolation to study the behavior of the response outside the calibration limits. Ignored if new_data is defined. Default = TRUE.
add_bar	(logical) whether to add bar legend. Default = TRUE.
add_limits	(logical) whether to add calibration limits if extrapolate = TRUE. Default = TRUE.
color_palette	(function) a color palette function to be used to assign colors in the plot. The default, NULL uses rev(hcl.colors(n, "terrain")).
xlab	(character) a label for the x axis. The default, NULL, uses the name defined in variable1.
ylab	(character) a label for the y axis. The default, NULL, uses the name defined in variable2.
...	additional arguments passed to image.

Value

A bivariate plot considering variable1 and variable2.

See Also

response_curve()

Examples

# Example with glmnet
# Import example of fitted_models (output of fit_selected())
data(fitted_model_maxnet, package = "kuenm2")

# Response curve (notice response affected by covariance)
bivariate_response(models = fitted_model_maxnet, modelID = "Model_219",
                   variable1 = "bio_1", variable2 = "bio_12")

# Example with glm
# Import example of fitted_models (output of fit_selected())
data(fitted_model_glm, package = "kuenm2")

# Response curve
bivariate_response(models = fitted_model_glm, modelID = "Model_85",
                   variable1 = "bio_1", variable2 = "bio_7")

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