EnsRps: Calculate the ensemble-adjusted Ranked Probability Score...

In sieste/SpecsVerification: Forecast Verification Routines for Ensemble Forecasts of Weather and Climate

Description

Calculate the ensemble-adjusted Ranked Probability Score (RPS) for categorical forecasts

Usage

EnsRps(ens, obs, R.new = NA, format = c("category", "members"))

FairRps(ens, obs, format = c("category", "members"))

Arguments

ens	matrix with N rows representing N time instances of categorical ensemble forecasts as follows: If 'format = category' (the default), then ens[t,r] indicates the category that the r-th ensemble member predicts for time t. If 'format = members', then ens[t,k] is the number of ensemble members that predict category k at time t.
obs	vector of length N, or matrix with N rows, representing the N observed category as follows: If ‘format = category’, obs is a vector and obs[t] is the category observed at time t. If 'format = members', obs is a matrix where obs[t,k] = 1 (and zero otherwise) if category k was observed at time t
R.new	ensemble size for which the scores should be adjusted, defaults to NA (no adjustment)
format	string, 'category' (default) or 'members' (can be abbreviated). See descriptions of arguments 'ens' and 'obs' for details.

Details

'FairRps(ens, obs)' returns 'EnsRps(ens, obs, R.new=Inf)'

Value

numeric vector of length N with the ensemble-adjusted RPS values

See Also

EnsBrier, EnsQs, EnsCrps

Examples

data(eurotempforecast)
EnsRps(ens.cat, obs.cat, R.new=Inf)

sieste/SpecsVerification documentation built on May 29, 2019, 9:59 p.m.