CRPS.RdThe 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, ...)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.
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
if (FALSE) ## Simulate data.
d <- GAMart()
## Model only including covariate x1.
b1 <- bamlss(num ~ s(x1), data = d)
#> Error in eval(expr, envir, enclos): object 'd' not found
## Now, also including x2 and x2.
b2 <- bamlss(num ~ s(x1) + s(x2) + s(x3), data = d)
#> Error in eval(expr, envir, enclos): object 'd' not found
## Compare using the CRPS score.
CRPS(b1)
#> Error in eval(expr, envir, enclos): object 'b1' not found
CRPS(b2)
#> Error in eval(expr, envir, enclos): object 'b2' not found