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 non-negativity of regression estimates. Options are:
|
varRule |
Method to control non-negativity 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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