MultiMetric {CSTools} | R Documentation |

## Multiple Metrics applied in Multiple Model Anomalies

### Description

This function calculates correlation (Anomaly Correlation Coefficient; ACC), root mean square error (RMS) and the root mean square error skill score (RMSSS) of individual anomaly models and multi-models mean (if desired) with the observations on arrays with named dimensions.

### Usage

```
MultiMetric(
exp,
obs,
metric = "correlation",
multimodel = TRUE,
time_dim = "ftime",
memb_dim = "member",
sdate_dim = "sdate"
)
```

### Arguments

`exp` |
A multidimensional array with named dimensions. |

`obs` |
A multidimensional array with named dimensions. |

`metric` |
A character string giving the metric for computing the maximum skill. This must be one of the strings 'correlation', 'rms' or 'rmsss. |

`multimodel` |
A logical value indicating whether a Multi-Model Mean should be computed. |

`time_dim` |
Name of the temporal dimension where a mean will be applied. It can be NULL, the default value is 'ftime'. |

`memb_dim` |
Name of the member dimension. It can be NULL, the default value is 'member'. |

`sdate_dim` |
Name of the start date dimension or a dimension name identifiying the different forecast. It can be NULL, the default value is 'sdate'. |

### Value

A list of arrays containing the statistics of the selected metric in
the element `$data`

which is a list of arrays: for the metric requested
and others for statistics about its signeificance. The arrays have two dataset
dimensions equal to the 'dataset' dimension in the `exp$data`

and
`obs$data`

inputs. If `multimodel`

is TRUE, the greatest position in
the first dimension correspons to the Multi-Model Mean.

### Author(s)

Mishra Niti, niti.mishra@bsc.es

Perez-Zanon Nuria, nuria.perez@bsc.es

### References

Mishra, N., Prodhomme, C., & Guemas, V. (n.d.). Multi-Model Skill Assessment of Seasonal Temperature and Precipitation Forecasts over Europe, 29-31. doi: 10.1007/s00382-018-4404-z

### See Also

### Examples

```
exp <- array(rnorm(2*2*4*5*2*2),
dim = c(dataset = 2, member = 2, sdate = 4, ftime = 5, lat = 2,
lon = 2))
obs <- array(rnorm(1*1*4*5*2*2),
dim = c(dataset = 1, member = 1, sdate = 4, ftime = 5, lat = 2,
lon = 2))
res <- MultiMetric(exp = exp, obs = obs)
```

*CSTools*version 5.2.0 Index]