ensembleBMA (version 2.0)

quantileForecastBMA: Quantile forecasts for ensemble BMA models.

Description

Computes quantiles for the probability distribution function (PDF) of an ensemble BMA mixture model.

Usage

quantileForecastBMA( object, ensembleData, quantiles = 0.5, 
                     popData = NULL, ...)

Arguments

object

An ensemble BMA model fit.

ensembleData

An ensembleData object giving including ensemble forecasts, observations and dates corresponding to object.

quantiles

The vector of desired quantiles for the PDF of the BMA mixture model.

popData

For ensembleBMAgamma0 and fitBMAgamma0 objects, there is an additional popData argument for providing predictors in the logistic regression for probability of precipitation. The value of popData

...

Included for generic function compatibility.

Value

• A vector of forecasts corresponding to the desired quantiles.

Details

This method is generic, and can be applied to any ensemble BMA forecasting model. Note the model may have been applied to a transformation of the data, but that information is included in the input object, and the output is transformed appropriately. This can be used to compute confidence intervals for the PDF.

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.

See Also

ensembleBMA, forecastBMA, gridForecastBMA, crpsANDmae

Examples

data(slp)

  slpData <- ensembleData(forecasts = slp[c("AVN","GEM","ETA","NGM","NOGAPS")],
                          observations = slp$obs, dates = slp$date)

  slpFit <- ensembleBMAnormal(slpData)

  slpForc <- quantileForecastBMA( slpFit, slpData)