rmse: Root Mean Squared Error (RMSE)

In insurancerating: Actuarial Tools for Insurance Pricing Models

Root Mean Squared Error (RMSE)

Description

Computes the root mean squared error (RMSE) for a fitted model, defined as the square root of the mean of squared differences between predictions and observed values.

Usage

rmse(x, data = NULL)

Arguments

x	A fitted model object (e.g. of class "glm").
data	A data frame containing the variables used in the model. Required if not already stored in object.

Details

The RMSE indicates the absolute fit of the model to the data. It can be interpreted as the standard deviation of the unexplained variance, and is expressed in the same units as the response variable. Lower values indicate better model fit.

Value

A numeric value: the root mean squared error.

Author(s)

Martin Haringa

Examples

x <- glm(nclaims ~ area, offset = log(exposure),
         family = poisson(), data = MTPL2)
rmse(x, MTPL2)

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