Description Usage Arguments Details Value See Also Examples

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

1 2 3 |

`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. |

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

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

EnsBrier, EnsQs, EnsCrps

1 2 |

```
1983 1984 1985 1986 1987
5.434783e-02 7.717391e-01 1.630435e-01 3.623188e-02 6.884058e-01
1988 1989 1990 1991 1992
1.630435e-01 3.297101e-01 5.543478e-01 3.260870e-02 4.347826e-01
1993 1994 1995 1996 1997
8.586957e-01 1.086957e-02 3.985507e-02 3.804348e-01 3.297101e-01
1998 1999 2000 2001 2002
2.173913e-02 5.434783e-02 5.543478e-01 1.304348e-01 9.384058e-01
2003 2004 2005 2006 2007
1.554348e+00 -3.035766e-18 1.992754e-01 2.028986e-01 1.992754e-01
2008 2009
5.434783e-02 2.173913e-02
```

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