| EnsRps {SpecsVerification} | R Documentation |
Calculate the ensemble-adjusted Ranked Probability Score (RPS) for categorical forecasts
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. Note that categories must be positive integers. 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)