CategoricalEnsCombination {CSTools}  R Documentation 
Make categorical forecast based on a multimodel forecast with potential for calibrate
Description
This function converts a multimodel ensemble forecast into a categorical forecast by giving the probability for each category. Different methods are available to combine the different ensemble forecasting models into probabilistic categorical forecasts.
See details in ?CST_CategoricalEnsCombination
Usage
CategoricalEnsCombination(fc, obs, cat.method, eval.method, amt.cat, ...)
Arguments
fc 
A multidimensional array with named dimensions containing the
seasonal forecast experiment data in the element named 
obs 
A multidimensional array with named dimensions containing the
observed data in the element named 
cat.method 
Method used to produce the categorical forecast, can be
either 
eval.method 
Is the sampling method used, can be either

amt.cat 
Is the amount of categories. Equallysized quantiles will be calculated based on the amount of categories. 
... 
Other parameters to be passed on to the calibration procedure. 
Value
An array containing the categorical forecasts in the element called
$data
. The first two dimensions of the returned object are named
dataset and member and are both of size one. An additional dimension named
category is introduced and is of size amt.cat.
Author(s)
Bert Van Schaeybroeck, bertvs@meteo.be
References
Rajagopalan, B., Lall, U., & Zebiak, S. E. (2002). Categorical climate forecasts through regularization and optimal combination of multiple GCM ensembles. Monthly Weather Review, 130(7), 17921811.
Robertson, A. W., Lall, U., Zebiak, S. E., & Goddard, L. (2004). Improved combination of multiple atmospheric GCM ensembles for seasonal prediction. Monthly Weather Review, 132(12), 27322744.
Van Schaeybroeck, B., & Vannitsem, S. (2019). Postprocessing of LongRange Forecasts. In Statistical Postprocessing of Ensemble Forecasts (pp. 267290).