Applies the refinement steps stored in a rating_refinement object and
returns a refitted GLM. This is the final step in the refinement workflow
after prepare_refinement(), add_smoothing(), add_restriction() or
add_relativities() have been used to define the proposed tariff structure.
Arguments
- object
Object of class
rating_refinement, usually created withprepare_refinement().- intercept_only
Logical. If
FALSE(default), fit the refined model with remaining model terms still free. IfTRUE, keep remaining existing relativities fixed as offsets and estimate only the intercept.- ...
Additional arguments passed to
stats::glm(), such ascontrol.
Value
A refitted object of class glm. The returned model also stores
attributes used by rating_table() and rating_grid() to recognise
refined rating factors, fixed relativities and smoothing metadata.
Details
Refinement steps are not applied to the fitted model immediately. They are
collected on the rating_refinement object so they can be inspected first,
for example with autoplot.rating_refinement(). refit() then applies the
steps in order, updates the model formula and data, and calls stats::glm()
with the original model family and any additional arguments passed through
....
With intercept_only = FALSE, the refined GLM is fitted with the remaining
free model terms that are still present after applying the refinement steps.
With intercept_only = TRUE, remaining original model effects are fixed as
offsets based on the existing fitted relativities. The refit then estimates
only the intercept. This can be useful when the relative tariff structure
should remain fixed and only the overall premium level should be recalibrated.
Examples
zip_df <- data.frame(
zip = c(0, 1, 2, 3),
zip_adj = c(0.8, 0.9, 1.0, 1.2)
)
model <- glm(
nclaims ~ zip + offset(log(exposure)),
family = poisson(),
data = MTPL
)
refined_model <- prepare_refinement(model) |>
add_restriction(zip_df) |>
refit(intercept_only = TRUE)