# CRPS: Continuous Rank Probability Score In bamlss: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)

 CRPS R Documentation

## 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. doi: 10.1198/016214506000001437cd ..

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)

## End(Not run)```

bamlss documentation built on April 8, 2022, 9:06 a.m.