controlMOSgev0 {ensembleMOS} | R Documentation |
Control parameters for censored generalized extreme value distribution EMOS models
Description
Specifies a list of values controling the censored generalized extreme value distribution EMOS fit of ensemble forecasts.
Usage
controlMOSgev0(optimRule = c("Nelder-Mead", "L-BFGS-B", "BFGS"),
coefRule = c("square", "none", "positive"),
varRule = c("square", "none"),
start = list(a = NULL, B = NULL,
s = NULL, c = NULL,
d = NULL, q = NULL),
maxIter = Inf)
Arguments
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. |
Details
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 :
, the
following generalized extreme value distribution EMOS
model left-censored at 0 is fit by
ensembleMOSgev0
:
where denotes the generalized extreme value distribution
left-censored at zero,
with location
, scale
and shape
. The model is
parametrized such that the mean
is a linear function
of the ensemble forecats, where
denotes the ratio of ensemble forecasts
that are exactly 0, and the shape parameter
is a linear
function of the ensemble variance
, where
is Gini's mean difference.
See ensembleMOSgev0 for details.
Value
A list whose components are the input arguments and their assigned values.
References
M. Scheuerer, Probabilistic quantitative precipitation forecasting using ensemble model output statistics. Quarterly Journal of the Royal Meteorological Society 140:1086–1096, 2014.
See Also
Examples
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 = "Nelder-Mead",
coefRule= "none",
varRule = "square"))