Description Usage Arguments Details Value References See Also Examples
Fits a truncated normal EMOS model to a given training set.
1 2 | fitMOStruncnormal(ensembleData, control = controlMOStruncnormal(),
exchangeable = NULL)
|
ensembleData |
An |
control |
A list of control values for the fitting functions specified via the function controlMOStruncnormal. For details and default values, see controlMOStruncnormal. |
exchangeable |
An optional numeric or character vector or factor indicating groups of
ensemble members that are exchangeable (indistinguishable).
The models have equal EMOS coefficients within each group.
If supplied, this argument will override any specification of
exchangeability in |
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. Specifically, a, b_1,…, b_m, c, d are
fitted to optimize
control$scoringRule
over the specified training period using
optim
with method = control$optimRule
.
A list with the following output components:
a |
The fitted intercept. |
B |
The fitted EMOS coefficients. |
c,d |
The fitted parameters for the squared scale, see details. |
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.
controlMOStruncnormal
,
ensembleMOStruncnormal
,
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | 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")
windTrain <- trainingData(windTestData, trainingDays = 30,
date = "2008010100")
windTestFit <- fitMOStruncnormal(windTrain)
|
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
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