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,
  data = NULL,
  extrapolation_type = "E",
  restricted_vars = NULL,
  type = "response"
)

Arguments

model

a glm object.

newdata

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

data

data.frame or matrix of data used in the model calibration step. Default = NULL.

extrapolation_type

(character) to indicate extrapolation type of model. Models can be transferred with three options: free extrapolation ('E'), extrapolation with clamping ('EC'), and no extrapolation ('NE'). Default = 'E'.

restricted_vars

(character) a vector containing the names of the variables that will undergo clamping or no extrapolation. For clamping, these variables are set to minimum and maximum values established for the max and min values within calibration values. For no extrapolation, the variables outside calibration limits became NA. If no specific names are provided, the value is set to NULL by default, indicating that clamping (EC) or no extrapolation (NE) will be applied to all variables. Ignore if extrapolation_type = 'E'.

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$glms_fitted$ModelID_7, newdata = env_vars,
                    data = sel_fit$data)
terra::plot(pred)