Add Model Predictions to a Data Frame — add_prediction • insurancerating

Adds predictions (and optionally confidence intervals) from one or more glm models to a data frame.

Usage

add_prediction(data, ..., var = NULL, conf_int = FALSE, alpha = 0.1)

Arguments

data: A data.frame containing the new data for which predictions should be generated.
...: One or more fitted model objects of class "glm".
var: Optional character vector giving names for the new prediction columns. Must have the same length as the number of models supplied. If NULL (default), names are generated automatically.
conf_int: Logical. If TRUE, add confidence intervals for predictions. Default is FALSE.
alpha: Numeric between 0 and 1. Controls the confidence level for interval estimates. Default is 0.10, corresponding to a 90% confidence interval.

Value

A data.frame containing the original data along with additional columns for model predictions (and confidence intervals if requested).

Author

Martin Haringa

Examples

mod1 <- glm(nclaims ~ age_policyholder,
            data = MTPL,
            offset = log(exposure),
            family = poisson())

# Add predicted values
mtpl_pred <- add_prediction(MTPL, mod1)

# Add predicted values with confidence bounds
mtpl_pred_ci <- add_prediction(MTPL, mod1, conf_int = TRUE)