Description Usage Arguments Details Value References See Also Examples
Fits a censored and shifted gamma EMOS model to ensemble forecasts for specified dates.
1 2 3 | ensembleMOScsg0(ensembleData, trainingDays, consecutive = FALSE,
dates = NULL, control = controlMOScsg0(),
warmStart = FALSE, exchangeable = NULL)
|
ensembleData |
An |
trainingDays |
An integer giving the number of time steps (e.g. days) in the training period. There is no default. |
consecutive |
If |
dates |
The dates for which EMOS forecasting models are desired.
By default, this will be all dates in |
control |
A list of control values for the fitting functions specified via the function controlMOScsg0. For details and default values, see controlMOScsg0. |
warmStart |
If |
exchangeable |
A numeric or character vector or factor indicating groups of
ensemble members that are exchangeable (indistinguishable).
The modeling will have equal parameters within each group.
The default determines exchangeability from |
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 Baran and Nemoda (2016) for details.
B
is a vector of fitted regression coefficients: b_1,
…, b_m. Specifically, a, b_1,…, b_m, c, d, q are
fitted to optimize
control$scoringRule
over the specified training period using
optim
with method = control$optimRule
.
A list with the following output components:
training |
A list containing information on the training length and lag and the number of instances used for training for each modeling date. |
a |
A vector of fitted EMOS intercept parameters for each date. |
B |
A matrix of fitted EMOS coefficients for each date. |
c,d |
The fitted parameters for the variance, see details. |
q |
Fitted shift parameter, see details. |
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 | 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")
fitDates <- c("2008010100", "2008010200")
prcpTestFitGEV0 <- ensembleMOSgev0(prcpTestData, trainingDays = 25,
dates = fitDates)
|
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
modeling for date 2008010100 ...
(Intercept) PCP24.gfs PCP24.cmcg PCP24.eta PCP24.gasp PCP24.jma
-0.19 0.07 0.00 0.11 0.04 0.30
PCP24.ngps PCP24.tcwb PCP24.ukmo
0.21 0.01 0.03 0.02
0.15 0.64 -0.37
modeling for date 2008010200 ...
(Intercept) PCP24.gfs PCP24.cmcg PCP24.eta PCP24.gasp PCP24.jma
-0.29 0.36 0.04 0.09 0.01 0.14
PCP24.ngps PCP24.tcwb PCP24.ukmo
0.12 0.02 0.08 0.31
0.05 1.61 -0.51
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