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Last data update: 2014.03.03

R: EMOS model fit to a training set

fitMOS

R Documentation

EMOS model fit to a training set

Description

Fits Ensemble Model Output Statistics to a given training set.

Usage

fitMOS(ensembleData, control = NULL, model = NULL,
       exchangeable = NULL)

Arguments

`ensembleData`	An `ensembleData` object including ensemble forecasts and verification observations. Missing values (indicated by `NA`) are allowed. Dates are ignored if they are included. This is the training set for the model.
`control`	A list of control values for the fitting functions. The default is `controlMOSnormal()` for Gaussian (normal) models.
`model`	A character string describing the EMOS model to be fit. Current choices are `"normal"`, typically used for temperature or pressure data. For specific details on model fitting see fitMOSnormal
`exchangeable`	A numeric or character vector or factor indicating groups of ensemble members that are exchangeable (indistinguishable). The model fit will have equal weights and parameters within each group. The default determines exchangeability from `ensembleData`.

Value

A list with the following output components:

`a`	The fitted intercept.
`B`	The fitted EMOS coefficients.
`c,d`	The fitted variance parameters for each date, see details.

References

T. Gneiting, A. E. Raftery, A. H. Westveld and T. Goldman, Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Monthly Weather Review 133:1098–1118, 2005.

Examples

  data(ensMOStest)

  ensNames <- c("gfs","cmcg","eta","gasp","jma","ngps","tcwb","ukmo")

  tempTestData <- ensembleData( forecasts = ensMOStest[,ensNames],
                                observations = ensMOStest[,"obs"],
                                station = ensMOStest[,"station"],
                                dates = ensMOStest[,"vdate"],
                                forecastHour = 48,
                                initializationTime = "00")

  tempTrain <- trainingData( tempTestData, trainingDays = 30,
                             date  = "2008010100")

  tempTrainFit <- fitMOS( tempTrain, model = "normal")

## equivalent to
##    tempTrainFit <- fitMOSnormal( tempTrain)