trainingData: Extract Training Data

In ensembleMOS: Ensemble Model Output Statistics

Description

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

Usage

trainingData(ensembleData, trainingDays, consecutive = FALSE, 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.
consecutive	If TRUE then dates in training set are treated as consecutive, i.e. date gaps are ignored.
date	The date for which the training data is desired.

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.
Available at: http://www.stat.washington.edu/research/reports/

C. Fraley, A. E. Raftery and T. Gneiting, Calibrating multi-model forecast ensembles with exchangeable and missing members using Bayesian model averaging, Monthly Weather Review 138:190-202, 2010.

See Also

ensembleMOSnormal, fitMOSnormal

Examples

data("ensBMAtest", package = "ensembleBMA")

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

obs <- paste("T2", "obs", sep = ".")
ens <- paste("T2", ensMemNames, sep = ".")
tempTestData <- ensembleData(forecasts = ensBMAtest[,ens],
                             dates = ensBMAtest[,"vdate"],
                             observations = ensBMAtest[,obs],
                             station = ensBMAtest[,"station"],
                             forecastHour = 48,
                             initializationTime = "00")

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

tempTrainFit <- fitMOSnormal(tempTrain)

Example output

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

ensembleMOS documentation built on May 2, 2019, 11:03 a.m.