rmse: Root Mean Squared Error

In MHaringa/actuarialpricing: Analytic Insurance Rating Techniques

Root Mean Squared Error

Description

Compute root mean squared error.

Usage

rmse(object, data)

Arguments

object	fitted model
data	data.frame (defaults to NULL)

Details

The RMSE is the square root of the average of squared differences between prediction and actual observation and indicates the absolute fit of the model to the data. It can be interpreted as the standard deviation of the unexplained variance, and is in the same units as the response variable. Lower values indicate better model fit.

Value

numeric value

Author(s)

Martin Haringa

Examples

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

MHaringa/actuarialpricing documentation built on Jan. 11, 2024, 1:13 a.m.