trainingData {ensembleBMA}R Documentation

Extract Training Data

Description

Extracts a subset of an ensembleData object corresponding to a given date and number of training days.

Usage

trainingData( ensembleData, trainingDays, date) 

Arguments

ensembleData An ensembleData object that includes, ensemble forecasts, observations and dates.
trainingDays An integer specifying the number of days in the training period.
date The date for which the training data is desired.

Details

The most recent days are used for training regardless of whether or not they are consecutive.

Value

An ensembleData object corresponding to the training data for the given date relative to ensembleData.

References

A. E. Raftery, T. Gneiting, F. Balabdaoui and M. Polakowski, Using Bayesian model averaging to calibrate forecast ensembles, Monthly Weather Review 133:1155-1174, 2005.

J. M. Sloughter, A. E. Raftery, T. Gneiting and C. Fraley, Probabilistic quantitative precipitation forecasting using Bayesian model averaging, Monthly Weather Review 135:3309–3320, 2007.

C. Fraley, A. E. Raftery, T. Gneiting and J. M. Sloughter, ensembleBMA: An R Package for Probabilistic Forecasting using Ensembles and Bayesian Model Averaging, Technical Report No. 516R, Department of Statistics, University of Washington, December 2008.

C. Fraley, A. E. Raftery, T. Gneiting, Using Bayesian Model Averaging to Calibrate Forecast Ensembles with Missing and Exchangeable Ensemble Members, (in preparation).

See Also

ensembleBMA, fitBMA

Examples

  data(ensBMAtest)

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

  obs <- paste("T2","obs", sep = ".")
  ens <- paste("T2", ensNames, sep = ".")

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

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


[Package ensembleBMA version 4.2 Index]