R: Unwrap Arguments and Hand Over to Verification Function

veriUnwrap {easyVerification} | R Documentation

## Unwrap Arguments and Hand Over to Verification Function

### Description

Decomposes input arguments into forecast, verifying observations, and reference forecast and hands these over to the function provided.

### Usage

    veriUnwrap(x, verifun, nind = c(nens = ncol(x) - 1, nref = 0, nobs = 1, nprob
      = 0, nthresh = 0), ref.ind = NULL, ...)

### Arguments

`x` | n x k + 1 matrix with n forecasts of k ensemble members plus the verifying observations
`verifun` | character string with function name to be executed
`nind` | named vector with number of ensemble members, ensemble members of reference forecasts, observations (defaults to 1), probability or absolute thresholds (see details)
`ref.ind` | list with specifications for the reference forecast (see details)
`...` | additional arguments passed on to `verifun`

### Details

Forecast verification metrics are only computed for forecasts with non-missing verifying observation and at least one non-missing ensemble member. Metrics for all other forecasts are set to missing. For aggregate metrics (e.g. skill scores) the metric is computed over non-missing observation/forecast pairs only.

For computation of skill scores, reference forecasts can be provided. That is, the first `nens` columns of `x` contain the forecasts, the `(nens + 1):(ncol(x) - 1)` following columns contain the reference forecast, and the final column contains the observations. If no reference forecast is provided (i.e. `ncol(x) == nens + 1`), a climatological forecast is constructed from the `n` verifying observations.

The elements of vector `nind` have to be named with `nens` containing the number of ensemble members, `nref` the number of ensemble members in the reference forecast for skill scores, `nobs` the number of observations (only one supported), `nprob` the number of probability thresholds, and `nthresh` the number of absolute threshold for conversion of continuous forecasts to category forecasts.

`ref.ind` specifies the set-up of the climatological reference forecast for skill scores if no explicit reference forecast is provided (see `indRef`). Also, `ref.ind` is used to determine the baseline to estimate the percentile-based category boundaries to convert continuous forecasts to category probabilities.

### Note

Out-of-sample reference forecasts are now fully supported.

### See Also

`veriApply`

[Package easyVerification version 0.4.4 Index]