Description Usage Arguments Details Value References See Also Examples
Specifies a list of values controling the censored generalized extreme value distribution EMOS fit of ensemble forecasts.
1 2 3 4 5 6 7 
optimRule 
Numerical optimization method to be supplied to 
coefRule 
Method to control nonnegativity of regression estimates. Options are:

varRule 
Method to control nonnegativity of the scale parameters.
Options 
start 
A list of starting parameters, 
maxIter 
An integer specifying the upper limit of the number of iterations used to fit the model. 
Note that only minimum CRPS estimation is available and chosen by default.
If no value is assigned to an argument, the first entry of the list of possibly choices will be used by default.
Given an ensemble of size m: X_1, … , X_m, the
following generalized extreme value distribution EMOS
model leftcensored at 0 is fit by ensembleMOSgev0
:
Y ~ GEV_0(μ,σ,q)
where GEV_0 denotes the generalized extreme value distribution leftcensored at zero, with location μ, scale σ and shape q. The model is parametrized such that the mean m is a linear function a + b_1 X_1 + … + b_m X_m + s p_0 of the ensemble forecats, where p_0 denotes the ratio of ensemble forecasts that are exactly 0, and the shape parameter σ is a linear function of the ensemble variance c + d MD(X_1,…,X_m), where MD(X_1,…,X_m) is Gini's mean difference. See ensembleMOSgev0 for details.
A list whose components are the input arguments and their assigned values.
M. Scheuerer, Probabilistic quantitative precipitation forecasting using ensemble model output statistics. Quarterly Journal of the Royal Meteorological Society 140:1086–1096, 2014.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19  data("ensBMAtest", package = "ensembleBMA")
ensMemNames < c("gfs","cmcg","eta","gasp","jma","ngps","tcwb","ukmo")
obs < paste("PCP24","obs", sep = ".")
ens < paste("PCP24", ensMemNames, sep = ".")
prcpTestData < ensembleData(forecasts = ensBMAtest[,ens],
dates = ensBMAtest[,"vdate"],
observations = ensBMAtest[,obs],
station = ensBMAtest[,"station"],
forecastHour = 48,
initializationTime = "00")
prcpTestFitGEV0 < ensembleMOSgev0(prcpTestData, trainingDays = 25,
dates = "2008010100",
control = controlMOSgev0(maxIter = as.integer(100),
optimRule = "NelderMead",
coefRule= "none",
varRule = "square"))

Loading required package: ensembleBMA
Loading required package: chron
Loading required package: evd
Attaching package: 'ensembleMOS'
The following objects are masked from 'package:ensembleBMA':
brierScore, cdf, crps, quantileForecast, trainingData
modeling for date 2008010100 ...
(Intercept) PCP24.gfs PCP24.cmcg PCP24.eta PCP24.gasp PCP24.jma
0.76 0.22 0.24 0.27 0.16 0.44
PCP24.ngps PCP24.tcwb PCP24.ukmo
0.17 0.03 0.32 0.85
0.24 1.02 0.02
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