# GaussCrps: Calculate the Continuous Ranked Probability Score (CRPS) for forecasts issued as Normal distributions

## Description

Calculate the Continuous Ranked Probability Score (CRPS) for forecasts issued as Normal distributions

## Usage

GaussCrps(mean, sd, obs)

## Arguments

mean

A vector of length N. The forecast means.

sd

A vector of length N. The forecast standard deviations.

obs

A numeric vector of length N of real-valued verifying observations

## Value

numeric vector of length N with the CRPS values

## References

Gneiting et al (2005). Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation. Mon. Wea. Rev. 10.1175/MWR2904.1

## See Also

EnsCrps, DressCrps, ScoreDiff, SkillScore

## Examples

# NOT RUN {
data(eurotempforecast)
mean <- rowMeans(ens)
sd <- apply(ens, 1, sd)
mean(GaussCrps(mean, sd, obs))
# }