brierScore {ensembleBMA} | R Documentation |
Computes Brier Scores for climatology, raw ensemble, and ensemble forecasting models given observation thresholds.
brierScore( fit, ensembleData, thresholds, dates = NULL, ...)
fit |
A model fit to ensemble forecasting data. |
ensembleData |
An ensembleData object including ensemble
forecasts, verification observations and 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.\
If ensembleData includes dates,
they must be consistent with fit and dates .
If ensembleData does not include dates, they will
be inferred from fit and 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 .
The dates are ignored if fit originates from fitBMA ,
which also ignores date information.
|
... |
Included for generic function compatibility. |
A data frame giving the Brier Scores for climatology
(empirical distribution of the verifying observations),
ensemble (voting), and ensemble foreacsting models
for the specified thresholds.
A logistic Brier score is also given for the BMAgamma0 model.
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. 516R, Department of Statistics, University of
Washington, 2009.
data(ensBMAtest) ensMemNames <- c("gfs","cmcg","eta","gasp","jma","ngps","tcwb","ukmo") obs <- paste("PCP24","obs", sep = ".") ens <- paste("PCP24", ensMemNames, sep = ".") prcpTestData <- ensembleData( forecasts = ensBMAtest[,ens], dates = ensBMAtest[,"vdate"], observations = ensBMAtest[,obs], station = ensBMAtest[,"station"], forecastHour = 48, initializationTime = "00") ## Not run: # R check prcpTestFit <- ensembleBMAgamma0( prcpTestData, trainingDays = 30) ## End(Not run) hist(prcpTestData$obs) brierScore(prcpTestFit, prcpTestData, thresholds = seq(from = 0, to = .5, by = .1))