afc.dp: 2AFC For Dichotomous Observations And Probabilistic Forecasts

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Routine to calculate the Generalized Discrimination Score (aka Two-Alternatives Forced Choice Score 2AFC) for the situation of dichotomous observations and discrete probabilistic forecasts

Usage

1
afc.dp(obsv, fcst)

Arguments

obsv

vector with dichotomous observations (values in 0,1)

fcst

vector of same length as obsv with forecast probabilities for the event to happen

Details

This routine applies Eq.5 of Mason and Weigel (2009) to calculate the 2AFC.

Value

p.afc

Value of Generalized Discrimination (2AFC) Score

Author(s)

Andreas Weigel, Federal Office of Meteorology and Climatology, MeteoSwiss, Zurich, Switzerland

References

S.J. Mason and A.P. Weigel, 2009. A generic verification framework for administrative purposes. Mon. Wea. Rev., 137, 331-349

See Also

afc

Examples

1
2
3
4
5
6
7
8
  #Forecasts and observations of Nino-3.4 index
  #Load set of dichotomous observations and probabilistic forecasts
  data(cnrm.nino34.dp)
  obsv = cnrm.nino34.dp$obsv
  fcst = cnrm.nino34.dp$fcst

  #Calculate skill score
  afc.dp(obsv,fcst)

afc documentation built on May 1, 2019, 9:46 p.m.