The function computes the continuous rank probability score (CRPS). Note that the function uses numerical integration, for highly efficient computation please see the scoringRules package.

CRPS(object, newdata = NULL,
interval = c(-Inf, Inf), FUN = mean,
term = NULL, ...)

## Arguments

object An object returned from bamlss. Optional new data that should be used for calculation. The interval that should be used for numerical integration Function to be applied on the CRPS scores. If required, specify the model terms that should be used within the predict.bamlss function. Arguments passed to function FUN.

## References

Gneiting T, Raftery AE (2007). Strictly Proper Scoring Rules, Prediction, and Estimation." Journal of the American Statistical Association, 102(477), 359--378. doi: 10.1198/016214506000001437 cd ..

Gneiting T, Balabdaoui F, Raftery AE (2007). Probabilistic Forecasts, Calibration and Sharpness. Journal of the Royal Statistical Society B, 69(2), 243--268. doi: 10.1111/j.1467-9868.2007.00587.x

## Examples

# NOT RUN {
## Simulate data.
d <- GAMart()

## Model only including covariate x1.
b1 <- bamlss(num ~ s(x1), data = d)

## Now, also including x2 and x2.
b2 <- bamlss(num ~ s(x1) + s(x2) + s(x3), data = d)

## Compare using the CRPS score.
CRPS(b1)
CRPS(b2)
# }