See the documentation for your object's class:
Arguments
- model
Statistical model.
- ...
Arguments passed to or from other methods, resp. for
compare_performance()
, one or multiple model objects (also of different classes).
Details
model_performance()
correctly detects transformed response and
returns the "corrected" AIC and BIC value on the original scale. To get back
to the original scale, the likelihood of the model is multiplied by the
Jacobian/derivative of the transformation.
See also
compare_performance()
to compare performance of many different models.
Examples
model <- lm(mpg ~ wt + cyl, data = mtcars)
model_performance(model)
#> # Indices of model performance
#>
#> AIC | AICc | BIC | R2 | R2 (adj.) | RMSE | Sigma
#> ---------------------------------------------------------------
#> 156.010 | 157.492 | 161.873 | 0.830 | 0.819 | 2.444 | 2.568
model <- glm(vs ~ wt + mpg, data = mtcars, family = "binomial")
model_performance(model)
#> # Indices of model performance
#>
#> AIC | AICc | BIC | Tjur's R2 | RMSE | Sigma | Log_loss | Score_log | Score_spherical | PCP
#> -----------------------------------------------------------------------------------------------------
#> 31.298 | 32.155 | 35.695 | 0.478 | 0.359 | 1.000 | 0.395 | -14.903 | 0.095 | 0.743