predict-ubmsFit-method function

Predict parameter values from a fitted model

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 signature 'ubmsFit'
predict(
  object,
  submodel,
  newdata = NULL,
  transform = TRUE,
  re.form = NULL,
  level = 0.95,
  ...
)

Arguments

• object: A fitted model of class ubmsFit
• submodel: Submodel to predict from, for example "det"
• newdata: Optional data frame, SpatRaster, or RasterStack of covariates to generate predictions from. If not provided (the default), predictions are generated from the original data
• transform: If TRUE, back-transform the predictions to their original scale
• re.form: If NULL, any estimated group-level parameters ("random effects") are included. If NA, they are ignored
• level: Probability mass to include in the uncertainty interval
• ...: Currently ignored

Returns

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.

See Also

posterior_linpred, posterior_interval