R: Calculate average score difference and assess uncertainty

ScoreDiff {SpecsVerification} | R Documentation

## Calculate average score difference and assess uncertainty

### Description

Calculate the difference (mean score of the reference forecast) minus (mean score of the forecast). Uncertainty is assessed by the Diebold-Mariano test for equality of predictive accuracy.

### Usage

    ScoreDiff(
      scores,
      scores.ref,
      N.eff = NA,
      conf.level = 0.95,
      handle.na = "na.fail"
    )

### Arguments

`scores` | vector of verification scores
`scores.ref` | vector of verification scores of the reference forecast, must be of the same length as 'scores'
`N.eff` | user-defined effective sample size to be used in hypothesis test and for confidence bounds; if NA, the length of 'scores' is used; default: NA
`conf.level` | confidence level for the confidence interval; default = 0.95
`handle.na` | how should missing values in scores vectors be handled; possible values are 'na.fail' and 'use.pairwise.complete'; default: 'na.fail'

### Value

vector with mean score difference, estimated standard error of the mean, one-sided p-value of the Diebold-Mariano test, and the user-specified confidence interval

### References

Diebold, Mariano (1995): Comparing Predictive Accuracy. Journal of Business & Economic Statistics. https://www.jstor.org/stable/1392185

### See Also

SkillScore

### Examples

    data(eurotempforecast)
    ScoreDiff(EnsCrps(ens, obs), EnsCrps(ens[, 1:2], obs))

[Package SpecsVerification version 0.5-3 Index]