rating_grid: Construct observed rating-grid points from model data or a...

In insurancerating: Actuarial Tools for Insurance Pricing Models

Construct observed rating-grid points from model data or a data frame

Description

rating_grid() constructs rating-grid points by collapsing rows with identical combinations of grouping variables to a single row.

The function returns only combinations that are actually observed in the input data. It does not create the full Cartesian product of all unique values. This keeps the output compact and suitable for model diagnostics, portfolio summaries, and prediction analysis.

When x is an object returned by extract_model_data(), the function uses the extracted model metadata to determine the grouping variables if group_by is not supplied. When x is a plain data.frame, it is recommended to supply group_by explicitly.

Usage

rating_grid(
  x,
  group_by = NULL,
  exposure = NULL,
  exposure_by = NULL,
  aggregate_cols = NULL,
  drop_na = FALSE,
  group_vars = NULL,
  agg_cols = NULL
)

Arguments

x	A data.frame, an object of class "model_data" returned by extract_model_data(), or a fitted model that can be passed to extract_model_data().
group_by	Optional character vector with the variables that define the rating-grid points. If NULL and x is a "model_data" object, the risk-factor variables stored in the object are used. If NULL and x is a plain data.frame, all columns except those listed in exposure, exposure_by, and aggregate_cols are used.
exposure	Optional character; name of the exposure column to aggregate.
exposure_by	Optional character; name of a column used to split exposure or counts, for example a year variable.
aggregate_cols	Optional character vector with additional numeric columns to aggregate using sum(na.rm = TRUE).
drop_na	Logical; if TRUE, rows with missing values in group_by are removed before aggregation. Default is FALSE.
group_vars, agg_cols	Deprecated argument names. Use group_by and aggregate_cols instead.

Details

The implementation uses base R only. Output is always a regular data.frame, not a tibble or data.table.

If exposure_by is supplied, exposure or row counts are split across levels of that variable and returned in wide format, for example "exposure_2020" or "count_2020".

For objects returned by extract_model_data(), refinement mappings are joined by their original factor column. They are not cross-joined onto every row.

Value

A data.frame with one row per observed rating-grid point.

Author(s)

Martin Haringa

Examples

## Not run: 
rating_grid(mtcars, group_by = c("cyl", "vs"))

rating_grid(
  mtcars,
  group_by = c("cyl", "vs"),
  exposure = "disp",
  exposure_by = "gear",
  aggregate_cols = "mpg"
)

pmodel <- glm(
  breaks ~ wool + tension,
  data = warpbreaks,
  family = poisson(link = "log")
)

pmodel |>
  extract_model_data() |>
  rating_grid()

## End(Not run)

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