CRPS: Continuous Rank Probability Score

In bamlss: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)

Continuous Rank Probability Score

Description

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.

Usage

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

Arguments

object	An object returned from bamlss.
newdata	Optional new data that should be used for calculation.
interval	The interval that should be used for numerical integration
FUN	Function to be applied on the CRPS scores.
term	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. \Sexpr[results=rd]{tools:::Rd_expr_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. \Sexpr[results=rd]{tools:::Rd_expr_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)

## End(Not run)

bamlss documentation built on March 19, 2024, 3:08 a.m.