Description Usage Arguments Details Value References See Also Examples
Specifies a list of values controling the truncated normal EMOS fit of ensemble forecasts.
1 2 3 4 5 6 7 
scoringRule 
The scoring rule to be used in optimum score estimation. Options are "crps" for the continuous ranked probability score and "log" for the logarithmic score. 
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. 
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 truncated normal model is fit by ensembleMOStruncnormal
:
Y ~ N_0(a + b_1 X_1 + ... + b_m X_m, c + dS^2),
where N_0 denotes the normal distribution truncated at zero,
with location a + b_1 X_1 + ... + b_m X_m and squared scale
c + dS^2.
B
is a vector of fitted regression coefficients b_1,
…, b_m. See ensembleMOStruncnormal for details.
A list whose components are the input arguments and their assigned values.
T. L. Thorarinsdottir and T. Gneiting, Probabilistic forecasts of wind speed: Ensemble model output statistics by using heteroscedastic censored regression. Journal of the Royal Statistical Society Series A 173:371–388, 2010.
ensembleMOStruncnormal
,
fitMOStruncnormal
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  data("ensBMAtest", package = "ensembleBMA")
ensMemNames < c("gfs","cmcg","eta","gasp","jma","ngps","tcwb","ukmo")
obs < paste("MAXWSP10","obs", sep = ".")
ens < paste("MAXWSP10", ensMemNames, sep = ".")
windTestData < ensembleData(forecasts = ensBMAtest[,ens],
dates = ensBMAtest[,"vdate"],
observations = ensBMAtest[,obs],
station = ensBMAtest[,"station"],
forecastHour = 48,
initializationTime = "00")
windTestFitTN < ensembleMOStruncnormal(windTestData, trainingDays = 25,
dates = "2008010100",
control = controlMOStruncnormal(maxIter = as.integer(100),
scoringRule = "log",
optimRule = "BFGS",
coefRule= "none",
varRule = "square"))

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