EnsSprErr: Spread to Error Ratio

Description Usage Arguments Details See Also Examples

View source: R/EnsSprErr.R

Description

Computes the spread to error ratio (SPR) for probabilistic forecasts - not unlike the functions in SpecsVerification. SPR > 1 indicates overdispersion (underconfidence), whereas SPR < indicates overconfidence in the forecasts.

Usage

1
EnsSprErr(ens, obs)

Arguments

ens

n x k matrix of n forecasts for k ensemble members

obs

vector with n verifying observations

Details

Here we define the spread-error rate as the square root of the ratio of mean ensemble variance to the mean squared error of the ensemble mean with the verifying observations

See Also

veriApply, FairSprErr

Examples

1
2
3
4
5
tm <- toymodel()
EnsSprErr(tm$fcst, tm$obs)

## compute spread to error ratio using veriApply
veriApply('EnsSprErr', fcst=tm$fcst, obs=tm$obs)

MeteoSwiss/easyVerification documentation built on May 10, 2017, 1:05 a.m.