brierScore {ensembleBMA} | R Documentation |
Computes climatology, ensemble, logistic, and BMA Brier scores given observation thresholds.
brierScore( fit, ensembleData, thresholds, dates = NULL, popData = NULL, ...)
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,
they must be consistent with fit and dates .
If ensembleData does not include dates, they will
be inferred from the fit and the dates argument.
|
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 fit , then popData of the
same kind must be supplied here.
|
... |
Included for generic function compatibility. |
There can be a lot of warnings due to logistic fitting near the extremes.
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.
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.
data(prcpTest) labels <- c("CENT","AVN","CMCG","ETA","GASP","JMA","NGPS","TCWB","UKMO") prcpTestData <- ensembleData( forecasts = prcpTest[ ,labels], dates = prcpTest$date, observations = prcpTest$obs) ## Not run: prcpTestFit <- ensembleBMAgamma0(prcpTestData) ## End(Not run) hist(prcpTestData$obs) brierScore(prcpTestFit, prcpTestData, thresholds = c(0, 5, 10, 15, 20))