ensembleMOS (version 0.8.2)

crps: Continuous Ranked Probability Score

Description

Computes the continuous ranked probability score (CRPS) for univariate ensemble forecasting models.

Usage

crps(fit, ensembleData, dates=NULL, …)

Arguments

fit

A model fit to ensemble forecasting data, obtained using fitMOS or ensembleMOS.

ensembleData

An ensembleData object that includes ensemble forecasts, verification observations and possibly dates. Missing values (indicated by NA) are allowed. This need not be the data used for the model fit, although it must include the same ensemble members.

dates

The dates for which the CRPS will be computed. These dates must be consistent with fit and ensembleData. The default is to use all of the dates in fit. The dates are ignored if fit originates from fitMOS, which also ignores date information.

…

Included for generic function compatibility.

Value

crps is a matrix giving the CRPS for each instance in the data for both the raw ensemble and the probabilistic forecast.

Details

These methods are generic, and can be applied to all ensemble forecasting models. Missing values in forecasts and/or observations result in NA values in the CRPS vector.

References

T. Gneiting and A. E. Raftery, Strictly proper scoring rules, prediction and estimation, Journal of the American Statistical Association 102:359--378, 2007.

See Also

ensembleMOS, fitMOS

Examples

# NOT RUN {
data("ensBMAtest", package = "ensembleBMA")

ensMemNames <- c("gfs","cmcg","eta","gasp","jma","ngps","tcwb","ukmo")

obs <- paste("T2", "obs", sep = ".")
ens <- paste("T2", ensMemNames, sep = ".")
tempTestData <- ensembleData(forecasts = ensBMAtest[,ens],
                             dates = ensBMAtest[,"vdate"],
                             observations = ensBMAtest[,obs],
                             station = ensBMAtest[,"station"],
                             forecastHour = 48,
                             initializationTime = "00")

tempTestFit <- ensembleMOS(tempTestData, trainingDays = 25, 
                           dates = "2008010100",
                           model = "normal")

crpsValues <- crps(tempTestFit, tempTestData)
colMeans(crpsValues)
# }