Description Usage Arguments Details Value References See Also Examples
Return decomposition of the Brier Score into Reliability, Resolution and Uncertainty, and estimated standard deviations
1 | BrierDecomp(p, y, bins = 10, bias.corrected = FALSE)
|
p |
vector of forecast probabilities |
y |
binary observations, y[t]=1 if an event happens at time t, and y[t]=0 otherwise |
bins |
binning to estimate the calibration function (see Details), default: 10 |
bias.corrected |
logical, default=FALSE, whether the standard (biased) decomposition of Murphy (1973) should be used, or the bias-corrected decomposition of Ferro (2012) |
To estimate the calibration curve, the unit line is categorised into discrete bins, provided by the 'bins' argument. If 'bins' is a single number, it specifies the number of equidistant bins. If 'bins' is a vector of values between zero and one, these values are used as the bin-breaks.
Estimators of the three components and their estimated standard deviations are returned as a 2*3 matrix.
Murphy (1973): A New Vector Partition of the Probability Score. J. Appl. Met. doi: 10.1175/1520-0450(1973)012<0595:ANVPOT>2.0.CO;2
Ferro and Fricker (2012): A bias-corrected decomposition of the Brier score. QJRMS. doi: 10.1002/qj.1924
Siegert (2013): Variance estimation for Brier Score decomposition. QJRMS. doi: 10.1002/qj.2228
ReliabilityDiagram
1 2 | data(eurotempforecast)
BrierDecomp(rowMeans(ens.bin), obs.bin, bins=3, bias.corrected=TRUE)
|
REL RES UNC
component 0.0004807685 0.11247520 0.25000000
component.sd 0.0160577293 0.04280087 0.01818475
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