Calculate density and integrated density function of a dressed ensemble forecast at a matrix of values

`GetDensity(dressed.ens, x, integrated = FALSE)`

dressed.ens

A list returned by the function `DressEnsemble`. See `?DressEnsemble` for details.

x

A matrix with either 1 row or nrow(dressed.ens[["ens"]]) rows and an arbitrary number of columns, holding the arguments at which the forecast distributions are to be evaluated. See Details.

integrated

logical, (default=FALSE): If `integrated` is TRUE, the integrated density (i.e. the value of the cumulative distribution function) is returned, otherwise the value of the density is returned.

The function returns a matrix, whose rows correspond to the individual ensemble forecasts and whose columns correspond to the values provided by the argument `x`.

If you want to evaluate each forecast distribution function at the same x-values, a matrix with one row can be provided, e.g. `x = matrix(c(-1, 0, 1), nrow=1)`

If the N individual forecast distributions are to be evaluated at different x-values, a matrix with N rows must be provided, where N is the number of time instances.

To calculate the PIT values for the dressed ensemble and observations `obs`, use `GetDensity(dressed.ens, x = matrix(obs, ncol=1), integrated=TRUE)`

DressEnsemble, DressCrps, DressIgn, PlotDressedEns, FitAkdParameters

# NOT RUN { data(eurotempforecast) dressed.ens <- DressEnsemble(ens) # calculate each density at the same x-values x1 <- matrix(seq(-3, 3, 0.1), nrow=1) dens1 <- GetDensity(dressed.ens, x1) # get the densities that the forecast # distributions assign to the observations x2 <- matrix(obs, ncol=1) dens2 <- GetDensity(dressed.ens, x2) # get the integrated densities that the forecast # distributions assign to the observations (useful # for constructing a PIT histogram) pit <- GetDensity(dressed.ens, x2, integrated=TRUE) # }