predict_glm {enmpa}

Extension of glm predict to generate predictions of different types

Description

Obtains predictions from a fitted generalized linear model objects. It also allows the clamping option to restrict extrapolation in areas outside the calibration area.

Usage

predict_glm(
  model,
  newdata,
  clamping = FALSE,
  var_to_clamp = NULL,
  type = "response"
)

Arguments

model

a glm object.

newdata

a data.frame or matrix with the new data to project the predictions.

clamping

(logical) whether to clamp values to a minimum and maximum value, that are established for the max and min values within calibration values. Default = FALSE.

var_to_clamp

(character) a vector containing the names of the variables that will undergo clamping. By default, if no specific names are provided, the value is set to NULL, which indicates that clamping will be applied to all variables. Ignore if clamping = FALSE.

type

(character) the type of prediction required. For a default binomial model the default predictions are of log-odds (probabilities on logit scale). The default, "response", returns predicted probabilities.

Value

A SpatRaster object or a vector with predictions.

Examples

# Load fitted model
data("sel_fit", package = "enmpa")

# Load raster layers to be projected
env_vars <- terra::rast(system.file("extdata", "vars.tif", package = "enmpa"))

# Prediction
pred <- predict_glm(sel_fit$ModelID_7, newdata = env_vars)
terra::plot(pred)