R: Area Under the ROC Curve

EnsRoca {easyVerification} | R Documentation

## Area Under the ROC Curve

### Description

Computes the area under the ROC curve given the observations. `EnsRoca` computes the Area Under the Curve (AUC). For ease of interpretation, `EnsRocss` converts the AUC to the range from -1 to 1 with zero indicating a forecast with no discrimination.

### Usage

    EnsRoca(ens, obs, use.easy = FALSE)

    EnsRocss(ens, obs, use.easy = FALSE)

### Arguments

`ens` | n x j matrix of n probability forecasts for j categories
`obs` | n x j matrix of occurence of n verifying observations in j categories
`use.easy` | logical, should implementation of standard errors as implemented in `easyVerifcation` be used (see below)?

### Standard Error

If used with `SpecsVerification >= 0.5`, the standard errors as implemented in the function `SpecsVerification::Auc` are used.

If `use.easy = TRUE` or when used with an older version of `SpecsVerification`, the standard error σ of the ROC area skill score is given by the following formula after Broecker (2012).

σ^2 = 1/3 (1/N0 + 1/N1 + 1/(N0 N1))

Where σ is the standard error, N1 the number of events, and N0 the number of non-events in category `i`.

### References

Broecker, J. (2012). Probability forecasts. Forecast Verification: A Practitioner's Guide in Atmospheric Science, Second Edition, 119-139.

### See Also

`veriApply`, `EnsRocss`

### Examples

    tm <- toymodel()

    ## compute ROC area for tercile forecasts using veriApply
    veriApply("EnsRoca", fcst=tm$fcst, obs=tm$obs, prob=1:2/3)

[Package easyVerification version 0.4.4 Index]