# EnsRps: 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.

## Value

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

## Details

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

## See Also

EnsBrier, EnsQs, EnsCrps

## Examples

# NOT RUN {
data(eurotempforecast)
EnsRps(ens.cat, obs.cat, R.new=Inf)
# }