edit_smoothing: Edit an existing smoothing step in a refinement workflow

In insurancerating: Actuarial Tools for Insurance Pricing Models

Edit an existing smoothing step in a refinement workflow

Description

Manually adjusts a smoothing step that was previously added with add_smoothing(). This is intended for actuarial review of a smoothed tariff curve, for example to flatten an unstable segment, align the end points of an interval, or add extra control points where expert judgement should guide the curve. The adjusted smoothing is applied when refit() is called.

Usage

edit_smoothing(
  model,
  model_variable = NULL,
  step = NULL,
  from,
  to,
  from_value = NULL,
  to_value = NULL,
  control_positions = NULL,
  control_values = NULL,
  allow_extrapolation = FALSE,
  extrapolation_step = NULL
)

Arguments

model	Object of class rating_refinement, created with prepare_refinement() and containing an existing smoothing step. Ordinary and refitted GLMs are not accepted directly. Legacy smooth and restricted objects are still accepted for backwards compatibility.
model_variable	Character string. The model_variable of the smoothing step to edit. Required when more than one smoothing step exists and step is not supplied.
step	Optional numeric index of the smoothing step to edit.
from, to	Numeric values giving the start and end of the source-variable interval to modify.
from_value, to_value	Optional numeric values used to override the smoothed curve value at from and to.
control_positions, control_values	Optional numeric vectors of equal length. These define additional points that the edited smoothing curve should pass through.
allow_extrapolation	Logical. Whether edits may extend beyond the observed source-variable range.
extrapolation_step	Optional positive numeric scalar used to set the spacing of extra break points when extrapolation is allowed.

Details

Use model_variable or step to identify the smoothing step to edit. The interval from from to to defines the part of the source variable range that should be changed. from_value and to_value can be used to force the curve values at the interval boundaries. control_positions and control_values add additional points that the edited curve should follow inside the interval.

edit_smoothing() changes the stored smoothing specification; it does not edit a fitted GLM in place. Keep the rating_refinement object, call refit() to assess the current specification, edit that same refinement object, and call refit() again. The previously fitted model remains an unchanged model result. This separation makes the sequence of actuarial adjustments reproducible and avoids reconstructing refinement choices from transformed columns in a refitted model.

Value

Object of class rating_refinement.

Author(s)

Martin Haringa

Examples

set.seed(42)
driver_age <- rep(seq(20, 59), each = 4)
exposure <- rep(1, length(driver_age))
age_band <- cut(
  driver_age,
  breaks = c(18, 30, 40, 50, 60),
  include.lowest = TRUE
)
expected_claims <- exp(
  -1.7 + 0.018 * (driver_age - 20) + 0.0006 * (driver_age - 40)^2
)
portfolio <- data.frame(
  claims = rpois(length(driver_age), exposure * expected_claims),
  exposure = exposure,
  driver_age = driver_age,
  age_band = age_band
)

model <- glm(
  claims ~ age_band + offset(log(exposure)),
  family = poisson(),
  data = portfolio
)

refinement <- prepare_refinement(model, data = portfolio) |>
  add_smoothing(
    model_variable = "age_band",
    source_variable = "driver_age",
    breaks = c(18, 30, 40, 50, 60),
    degree = 2,
    weights = "exposure"
  )

# Fit and inspect the initial smoothing specification.
initial_model <- refit(refinement)

# Edit the retained specification and fit it again.
refinement <- refinement |>
  edit_smoothing(
    model_variable = "age_band",
    from = 30,
    to = 50,
    from_value = 1.00,
    to_value = 1.10,
    control_positions = c(40),
    control_values = c(1.05)
  )

refined_model <- refit(refinement)

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