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Bivariate response plot for fitted models

bivariate_response.Rd

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_13",
                   variable1 = "bio_1", variable2 = "bio_12")
#> Error in bivariate_response(models = fitted_model_maxnet, modelID = "Model_13",     variable1 = "bio_1", variable2 = "bio_12"): Defined 'variable1' is not present in the models model.

# 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_1",
                   variable1 = "bio_1", variable2 = "bio_7")
#> Error in bivariate_response(models = fitted_model_glm, modelID = "Model_1",     variable1 = "bio_1", variable2 = "bio_7"): Defined 'variable1' is not present in the models model.