refit: Refit a prepared refinement workflow

In insurancerating: Actuarial Tools for Insurance Pricing Models

Refit a prepared refinement workflow

Description

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.

Usage

refit(object, intercept_only = FALSE, ...)

Arguments

object	Object of class rating_refinement, usually created with prepare_refinement().
intercept_only	Logical. If FALSE (default), fit the refined model with remaining model terms still free. If TRUE, keep remaining existing relativities fixed as offsets and estimate only the intercept.
...	Additional arguments passed to stats::glm(), such as control.

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.

Printing the returned model first shows the original and refitted formulas, the model family, whether an intercept-only refit was used, and a concise description of every restriction, smoothing or relativity step. This is followed by the regular glm output with the model call, coefficients, degrees of freedom, deviance and AIC. The object continues to inherit from glm, so standard methods such as stats::predict.glm() and summary.glm() remain available.

Value

A refitted object that inherits from glm and additionally from refitrestricted, refitsmooth, or both, depending on the applied refinement steps. The returned model stores attributes used by rating_table() and rating_grid() to recognise refined rating factors, fixed relativities and smoothing metadata.

Author(s)

Martin Haringa

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)

insurancerating documentation built on July 30, 2026, 5:09 p.m.