predict.disag_model {disaggregation}  R Documentation 
predict.disag_model function takes a disag_model object created by disaggregation::disag_model and predicts mean and uncertainty maps.
## S3 method for class 'disag_model'
predict(object, newdata = NULL, predict_iid = FALSE, N = 100, CI = 0.95, ...)
object 
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. 
predict_iid 
logical. 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 to be calculated from the realisations. Default: 0.95. 
... 
Further arguments passed to or from other methods. 
To predict over a different spatial extent to that used in the model, a RasterStack 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.
For the uncertainty calculations, the number of the realisations and the size of the confidence interval to be calculated are given by the arguments N and CI respectively.
An object of class disag_prediction which consists of a list of two objects:
mean_prediction 
List of:

uncertainty_prediction: 
List of:

## Not run:
predict(fit_result)
## End(Not run)