Augment data with predictions

augment(), unlike forecast(), has the goal of modifying the training data, rather than just producing new forecasts. It does a prediction on new_data, which will produce a prediction for most time_values, and then adds .pred as a column to new_data and returns the resulting join.

Usage

# S3 method for class 'epi_workflow'
augment(x, new_data, ...)

Arguments

x

A trained epi_workflow

new_data

A epi_df of predictors

...

Arguments passed on to the predict method.

Value

new_data with additional columns containing the predicted values