brier {verification} | R Documentation

## Brier Score

### Description

Calculates verification statistics for probabilistic forecasts of binary events.

### Usage

        brier(obs, pred, baseline, thresholds = seq(0,1,0.1), bins = TRUE, ... )

### Arguments

`obs` | Vector of binary observations
`pred` | Vector of probablistic predictions [0,1]
`baseline` | Vector of climatological (no - skill) forecasts. If this is null, a sample climatology will be calculated.
`thresholds` | Values used to bin the forecasts. By default the bins are {[0,0.1), [0.1, 0.2), ....} .
`bins` | 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

### Value

`baseline.tf` | Logical indicator of whether climatology was provided.
`bs` | Brier score
`bs.baseline` | Brier Score for climatology
`ss` | Skill score
`bs.reliability` | Reliability portion of Brier score.
`bs.resolution` | Resolution component of Brier score.
`bs.uncert` | Uncertainty component of Brier score.
`y.i` | Forecast bins – described as the center value of the bins.
`obar.i` | Observation bins – described as the center value of the bins.
`prob.y` | Proportion of time using each forecast
`obar` | Forecast based on climatology or average sample observations.
`check` | Reliability - resolution + uncertainty should equal brier score.

### Note

This function is used within `verify`.

### Author(s)

Matt Pocernich <pocernic@rap.ucar.edu>

### References

Wilks, D. S. (1995) Statistical Methods in the Atmospheric Sciences Chapter 7, San Diego: Academic Press.

### Examples

    #  probabilistic/ binary example

    pred<- runif(100)
    obs<- round(runif(100))
    brier(obs, pred)

[Package verification version 1.20 Index]