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easyVerification (version 0.1.8)

Ensemble Forecast Verification for Large Datasets

Description

Set of tools to simplify application of atomic forecast verification metrics for (comparative) verification of ensemble forecasts to large datasets. The forecast metrics are imported from the 'SpecsVerification' package, and additional forecast metrics are provided with this package. Alternatively, new user-defined forecast scores can be implemented using the example scores provided and applied using the functionality of this package.

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Version

Install

install.packages('easyVerification')

Monthly Downloads

483

Version

0.1.8

License

GPL-3

Maintainer

Jonas Bhend

Last Published

October 15th, 2015

Functions in easyVerification (0.1.8)

toymodel

Create example forecast-observation pairs
convert2prob

Convert to probability / categorical forecast
EnsError

Compute various ensemble mean error metrics
EnsRoca

Area under the ROC curve
EnsSprErr

Compute spread-error ratio
EnsCorr

Ensemble mean correlation
EnsErrorss

Compute various ensemble mean error skill scores
easyVerification

easyVerification.
EnsRocss

Skill score for area under the ROC curve
Ens2AFC

Generalized discrimination score
FairSprErr

Fair spread-error ratio
count2prob

Convert counts to probabilities
veriApply

Apply verification metrics to large datasets
veriUnwrap

Unwrap arguments and hand over to function