Description Usage Arguments Details Value Author(s) References Examples
Decomposes the empirical Brier score into reliability, resolution and uncertainty. Two different estimators for the components are provided: The original estimators proposed by Murphy (1974), and the bias-corrected estimators proposed by Ferro and Fricker (2012). Sampling variances of all the components are estimated. This package applies only to probabilistic predictions of binary events.
1 |
p |
a vector of forecast probabilities. No default. |
y |
a vector of binary event indicators. No default. |
n.bins |
number of bins used for calculating the calibration function. Default |
... |
possible additional arguments. Not used at the moment. |
The values of the forecast probabilities in p
are binned into n.bins
bins of equal length on the unit interval. All probabilities are replaced with their in-bin average. Based on this binning, the calibration function P(y=1|p) is estimated, which is required to estimate the components of the Brier Score decomposition of p
.
An object of class bride
, essentially a list containing:
p,y |
the objects of the original request. |
n.bins |
number of equidistant, exhaustive bins used to calculate the cross table. |
rel,res,unc |
reliability, resolution, uncertainty estimates derived by Murphy (1970). |
rel2,res2,unc2 |
bias-corrected reliability, resolution, uncertainty estimates derived by Ferro and Fricker (2012). |
rel.var,res.var,unc.var,rel2.var,res2.var,unc2.var |
variance estimators derived by Siegert (2013). |
Stefan Siegert
Murphy, AH (1974) A new vector partition of the probability score, Journal of Applied Meteorology, 12:595-600
Ferro CAT, Fricker TE (2012) A bias-corrected decomposition of the Brier Score, Quarterly Journal of the Royal Meteorological Society, 138(668): 1954-1960
Siegert, S. (2013) Variance estimation for Brier Score decomposition, http://arxiv.org/abs/1303.6182
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