Description Usage Arguments Details Value References See Also Examples
Specifies a list of values controling the censored and shifted gamma 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.
Note that optimMethod options are only available for scoringRule = "log"
.
In case of scoringRule = "crps"
, the optimization method
is set to "L-BFGS-B" by default.
Given an ensemble of size m: X_1, … , X_m, the
following shifted gamma model left-censored at 0
is fit by ensembleMOScsg0
:
Y ~ Gamma_0(κ,θ,q)
where Gamma_0 denotes the shifted gamma distribution left-censored at zero, with shape κ, scale θ and shift q. The model is parametrized such that the mean κθ is a linear function a + b_1 X_1 + … + b_m X_m of the ensemble forecats, and the variance κθ^2 is a linear function of the ensemble mean c+d \overline{f}, see ensembleMOScsg0 for details.
A list whose components are the input arguments and their assigned values.
M. Scheuerer and T. M. Hamill, Statistical post-processing of ensemble precipitation forecasts by fitting censored, shifted gamma distributions. Monthly Weather Review 143:4578–4596, 2015.
S. Baran and D. Nemoda, Censored and shifted gamma distribution based EMOS model for probabilistic quantitative precipitation forecasting. Environmetrics 27:280–292, 2016.
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("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")
prcpTestFitCSG0 <- ensembleMOScsg0(prcpTestData, trainingDays = 25,
dates = "2008010100",
control = controlMOScsg0(maxIter = as.integer(100),
scoringRule = "log",
optimRule = "Nelder-Mead",
coefRule= "none",
varRule = "square"))
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