Calculates verification statistics for probabilistic forecasts of binary events.
brier(obs, pred, baseline, thresholds = seq(0,1,0.1), bins = TRUE, ... )
Logical indicator of whether climatology was provided.
Brier score
Brier Score for climatology
Skill score
Reliability portion of Brier score.
Resolution component of Brier score.
Uncertainty component of Brier score.
Forecast bins -- described as the center value of the bins.
Observation bins -- described as the center value of the bins.
Proportion of time using each forecast
Forecast based on climatology or average sample observations.
Reliability - resolution + uncertainty should equal brier score.
Vector of binary observations
Vector of probablistic predictions [0,1]
Vector of climatological (no - skill) forecasts. If this is null, a sample climatology will be calculated.
Values used to bin the forecasts. By default the bins are {[0,0.1), [0.1, 0.2), ....} .
If TRUE, thresholds define bins into which the probablistic forecasts are entered and assigned the midpoint as a forecast. Otherwise, each unique forecast is considered as a seperate forecast. For example, set bins to FALSE when dealing with a finite number of probabilities generated by an ensemble forecast.
Optional arguments
Matt Pocernich
Wilks, D. S. (1995) Statistical Methods in the Atmospheric Sciences Chapter 7, San Diego: Academic Press.
# probabilistic/ binary example
pred<- runif(100)
obs<- round(runif(100))
brier(obs, pred)
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