afc-package: Generalized Discrimination Score 2AFC

Description Details Index Author(s) References

Description

This package is a collection of routines to calculate the "generalized discrimination score", which is also known as "two alternatives forced-choice score" or short: "2AFC-score". The 2AFC is a generic forecast verification framework which can be applied to any of the following verification contexts: dichotomous, polychotomous (ordinal and nominal), continuous, probabilistic, and ensemble. A comprehensive description of the 2AFC-score, including all equations used in this package, is provided by Mason and Weigel (2009).

Details

The master routine is afc. For a given set of observation and forecast data, and for a specified verification context, afc calls the appropriate functions which are necessary to calculate the 2AFC score.

Why the 2AFC-score? There are numerous reasons for calculating forecast verification scores, and considerable attention has been given to designing and analyzing the properties of scores that can be used for scientific purposes. Much less attention has been given to scores that may be useful for administrative reasons, such as communicating changes in forecast quality to bureaucrats, and providing indications of forecast quality to the general public. The 2AFC test a scoring procedure that is sufficiently generic to be useable on forecasts ranging from simply "yes"/"no" forecasts of dichotomous outcomes to continuous variables, and can be used with deterministic or probabilistic forecasts without seriously reducing the more complex information when available. Although, as with any single verification score, the 2AFC has limitations, it does have broad intuitive appeal in that the expected score of an unskilled set of forecasts (random guessing or perpetually identical forecasts) is 50%, and is interpretable as an indication of how often the forecasts are correct, even when the forecasts are expressed probabilistically and/or the observations are not discrete.

Package: afc
Version: 1.03
Date: 2010-01-07
License: GPL-2

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afc                     Calculate Generalized Discrimination Score 2AFC
afc-package             Generalized Discrimination Score 2AFC
afc.cc                  2AFC For Continuous Observations And Continuous 
                        Forecasts
afc.ce                  2AFC For Ordinal Polychotomous Observations And
                        Ensemble Forecasts
afc.dc                  2AFC For Dichotomous Observations And
                        Continuous Forecasts
afc.dd                  2AFC For Dichotomous Observations And
                        Dichotomous Forecasts
afc.de                  2AFC for Dichotomous Observations and Ensemble
                        Forecasts
afc.dm                  2AFC For Dichotomous Observations And
                        Polychotomous Forecasts
afc.dp                  2AFC For Dichotomous Observations And
                        Probabilistic Forecasts
afc.mc                  2AFC For Ordinal Polychotomous Observations And
                        Continuous Forecasts
afc.me                  2AFC For Ordinal Polychotomous Observations And
                        Ensemble Forecasts
afc.mm                  2AFC For Ordinal Polychotomous Observations And
                        Ordinal Polychotomous Forecasts
afc.mp                  2AFC For Ordinal Polychotomous Observations And
                        Probabilistic Forecasts
afc.nn                  2AFC For Nominal Polychotomous Observations And
                        Nominal Polychotomous Forecasts
afc.np                  2AFC For Nominal Polychotomous Observations And
                        Probabilistic Forecasts
cnrm.nino34.cc          Example Data of Continuous Observations and
                        Continuous Forecasts
cnrm.nino34.ce          Example Data of Continuous Observations and 
                        Ensemble Forecasts
cnrm.nino34.dc          Example Data of Dichotomous Observations and
                        Continuous Forecasts
cnrm.nino34.dd          Example Data of Dichotomous Observations and
                        Dichotomous Forecasts
cnrm.nino34.de          Example Data of Dichotomous Observations and
                        Ensemble Forecasts
cnrm.nino34.dm          Example Data of Dichotomous Observations and
                        Polychotomous Forecasts
cnrm.nino34.dp          Example Data of Dichotomous Observations and
                        Polychotomous Forecasts
cnrm.nino34.mc          Example Data of Polychotomous Observations and
                        Continuous Forecasts
cnrm.nino34.me          Example Data of Polychotomous Observations and
                        Ensembles Forecasts
cnrm.nino34.mm          Example Data of Polychotomous Observations and
                        Polychotomous Forecasts
cnrm.nino34.mp          Example Data of Polychotomous Observations and
                        Probabilistic Forecasts
rank.ensembles          Rank Ensembles

Author(s)

Andreas Weigel, Federal Office of Meteorology and Climatology (MeteoSwiss), Zurich, Switzerland <andreas.weigel@meteoswiss.ch>

References

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


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