ensembleBMA (version 2.1)

brierScore: Brier Scores

Description

Computes climatology, ensemble, logistic, and BMA Brier scores given observation thresholds.

Usage

brierScore( fit, ensembleData, thresholds, dates = NULL, popData = NULL, 
                ...)

Arguments

fit

An ensemble BMA model fit for ensembleData.

ensembleData

An ensembleData object including ensemble forecasts and observations. It need not be the object used to form fit, although it must include the same ensemble members. If ensembleData includes dates,

thresholds

One or more threshold values for the Brier score computations.

dates

The dates for which the Brier score will be computed. These dates must be consistent with fit and ensembleData. The default is to use all of the dates in fit.

popData

For gamma0 model fits, there is an additional popData argument for providing predictors in the logistic regression for probability of zero precipitation. If popData was supplied to obtain in the modeling for

...

Included for generic function compatibility.

Value

• A data frame giving the climatology (empirical distribution of the verifying observations), ensemble (voting), logistic (coefficients determined by logistic regression on the training data), and BMA Brier scores for the specified thresholds.

Details

There can be a lot of warnings due to logistic fitting near the extremes.

References

G. W. Brier, Verification of forecasts expressed in terms of probability, Monthly Weather Review, 78:1--3 (1950).

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

C. Fraley, A. E. Raftery, T. Gneiting and J. M. Sloughter, ensembleBMA: An R Package for Probabilistic Forecasting using Ensembles and Bayesian Model Averaging, Technical Report No. 516, Department of Statistics, University of Washington, August 2007.

See Also

ensembleBMA

Examples

data(prcpTest)
                                      
  labels <- c("CENT","AVN","CMCG","ETA","GASP","JMA","NGPS","TCWB","UKMO")
  prcpTestData <- ensembleData( forecasts = prcpTest[ ,labels],
                          dates = prcpTest$date, observations = prcpTest$obs)
prcpTestFit <- ensembleBMAgamma0(prcpTestData)
 
  hist(prcpTestData$obs)

  brierScore(prcpTestFit, prcpTestData, thresholds = c(0, 5, 10, 15, 20))