quantileForecastBMA {ensembleBMA} | R Documentation |
Computes quantiles for the probability distribution function (PDF) of an ensemble BMA mixture model.
quantileForecastBMA( object, ensembleData, quantiles = 0.5, popData = NULL, ...)
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 (if any) used to create object
should be supplied here.
|
... |
Included for generic function compatibility. |
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.
A vector of forecasts corresponding to the desired quantiles.
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.
ensembleBMA
,
forecastBMA
,
gridForecastBMA
,
crpsANDmae
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)