This method generates predicted parameter values for the original dataset or a new dataset using the posterior distribution. Standard deviation and a customizable uncertainty interval are also calculated.
# S4 method for class 'ubmsFit'
predict(
object,
submodel,
newdata = NULL,
transform = TRUE,
re.form = NULL,
level = 0.95,
...
)A fitted model of class ubmsFit
Submodel to predict from, for example "det"
Optional data frame, SpatRaster, or RasterStack of covariates to generate predictions from. If not provided (the default), predictions are generated from the original data
If TRUE, back-transform the predictions to their
original scale
If NULL, any estimated group-level parameters ("random
effects") are included. If NA, they are ignored
Probability mass to include in the uncertainty interval
Currently ignored
If newdata was a data frame: A data frame with one row per
prediction and four columns:
1) Predicted point estimates (posterior means),
2) Standard deviation of the posterior,
3-4) Lower and upper bounds of the specified uncertainty interval
For parameters with more than one dimension, the rows are in site-major order, or site-year-observation for dynamic models.
If newdata was a SpatRaster/RasterStack, returns a SpatRaster/RasterStack
with four layers corresponding to the four columns above with the same projection
as the original SpatRaster/RasterStack.
posterior_linpred, posterior_interval