autoplot.riskfactor_gam: Autoplot for GAM objects from 'risk_factor_gam()'

In insurancerating: Actuarial Tools for Insurance Pricing Models

Autoplot for GAM objects from risk_factor_gam()

Description

Generates a ggplot2 visualization of a fitted GAM created with risk_factor_gam(). The plot shows the fitted curve, and optionally confidence intervals and observed data points.

Usage

## S3 method for class 'riskfactor_gam'
autoplot(
  object,
  confidence = FALSE,
  color_gam = "steelblue",
  show_observations = FALSE,
  x_stepsize = NULL,
  size_points = 1,
  color_points = "black",
  rotate_labels = FALSE,
  remove_outliers = NULL,
  conf_int = NULL,
  ...
)

Arguments

object	An object of class "riskfactor_gam" returned by risk_factor_gam().
confidence	Logical. If TRUE, add 95% confidence intervals around the fitted curve. Default is FALSE.
color_gam	Color for the fitted GAM line, specified by name (e.g., "red") or hex code (e.g., "#FF1234"). Default is "steelblue".
show_observations	Logical. If TRUE, add observed frequency/severity points corresponding to the underlying data.
x_stepsize	Numeric. Step size for tick marks on the x-axis. If NULL, breaks are determined automatically.
size_points	Numeric. Point size for observed data. Default is 1.
color_points	Color for the observed data points. Default is "black".
rotate_labels	Logical. If TRUE, rotate x-axis labels by 45 degrees to reduce overlap.
remove_outliers	Numeric. If specified, observations greater than this threshold are omitted from the plot.
conf_int	Deprecated. Use confidence instead.
...	Additional arguments passed to underlying ggplot2 functions.

Value

A ggplot object representing the fitted GAM.

Author(s)

Martin Haringa

Examples

## Not run: 
library(ggplot2)
fit <- risk_factor_gam(MTPL,
                       risk_factor = "age_policyholder",
                       claim_count = "nclaims",
                       exposure = "exposure")

autoplot(fit, show_observations = TRUE)

## End(Not run)

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