Performance of fitted GLMs

Computes model performance indices for one or more fitted GLMs.

Usage

model_performance(...)

Arguments

...

One or more objects of class "glm".

Value

A data frame of class "model_performance", with columns:

Model

Name of the model object as passed to the function.

AIC

AIC value.

BIC

BIC value.

RMSE

Root mean squared error.

Details

The following indices are reported:

AIC

Akaike's Information Criterion.

BIC

Bayesian Information Criterion.

RMSE

Root mean squared error, computed from observed and predicted values.

This function is adapted from performance::model_performance().

Author

Martin Haringa

Examples

m1 <- glm(nclaims ~ area, offset = log(exposure), family = poisson(),
          data = MTPL2)
m2 <- glm(nclaims ~ area + premium, offset = log(exposure), family = poisson(),
          data = MTPL2)
model_performance(m1, m2)
#> # Comparison of Model Performance Indices
#> 
#> Model |   AIC    |   BIC    | RMSE  
#> ------+----------+----------+------ 
#>    m1 | 2285.729 | 2297.741 | 0.356 
#>    m2 | 2287.546 | 2305.566 | 0.356