predict_uncertainty {disaggregation}  R Documentation 
Function to predict uncertainty from the model result
Description
predict_uncertainty function takes a disag_model object created by disaggregation::disag_model and predicts upper and lower credible interval maps.
Usage
predict_uncertainty(
model_output,
newdata = NULL,
predict_iid = FALSE,
N = 100,
CI = 0.95
)
Arguments
model_output 
disag_model object returned by disag_model function. 
newdata 
If NULL, predictions are made using the data in model_output. If this is a raster stack or brick, predictions will be made over this data. Default NULL. 
predict_iid 
If TRUE, any polygon iid effect from the model will be used in the prediction. Default FALSE. 
N 
number of realisations. Default: 100. 
CI 
confidence interval. Default: 0.95. 
Details
Function returns a SpatRaster of the realisations as well as the upper and lower credible interval rasters.
To predict over a different spatial extent to that used in the model, a SpatRaster covering the region to make predictions over is passed to the argument newdata. If this is not given predictions are made over the data used in the fit.
The predict_iid logical flag should be set to TRUE if the results of the iid effect from the model are to be used in the prediction.
The number of the realisations and the size of the confidence interval to be calculated. are given by the arguments N and CI respectively.
Value
The uncertainty prediction, which is a list of:

realisations SpatRaster of realisations of predictions. Number of realisations defined by argument N.

predictions_ci SpatRaster of the upper and lower credible intervals. Defined by argument CI.
Examples
## Not run:
predict_uncertainty(result)
## End(Not run)