fitBMAgamma0 {ensembleBMA} | R Documentation |
Fits a Bayesian Modeling Averaging mixture of gammas with a point mass at 0 to a given training set. Intended for precipitation forecasts.
fitBMAgamma0( ensembleData, control = controlBMAgamma0(), exchangeable = NULL)
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 defaults are
given by the function controlBMAgamma0 .
|
exchangeable |
An optional 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.
If supplied, this argument will override any specification of
exchangeability in ensembleData .
|
This function fits a BMA model to a training data set.
It is called by ensembleBMAgamma0
, which can produce a sequence
of fits over a larger precipitation data set.
Methods available for the output of fitBMA
include:
cdf
, quantileForecast
, and
modelParameters
.
A list with the following output components:
prob0coefs |
The fitted coefficients in the model for the point mass at 0 (probability of zero precipitation) for each member of the ensemble. |
biasCoefs |
The fitted coefficients in the model for the mean of nonzero observations for each member of the ensemble (used for bias correction). |
varCoefs |
The fitted coefficients for the model for the variance of nonzero observations (these are the same for all members of the ensemble). |
weights |
The fitted BMA weights for the gamma components for each ensemble member. |
nIter |
The number of EM iterations. |
transformation |
The function corresponding to the transformation of the data used to fit
the models for the point mass at 0 and mean of nonzero observations.
The untransformed forecast is used to fit the variance model.
This is input as part of control .
|
inverseTransformation |
The function corresponding to the inverse of transformation .
Used for quantile forecasts and verification.
This is input as part of control .
|
J. M. Sloughter, A. E. Raftery, T. Gneiting and C. Fraley, Probabilistic quantitative precipitation forecasting using Bayesian model averaging, Monthly Weather Review 135:3209–3220, 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, May 2008.
C. Fraley, A. E. Raftery, T. Gneiting, BMA Forecasting with Missing and Exchangeable Ensemble Members, in preparation
ensembleData
,
controlBMAgamma0
,
ensembleBMAgamma0
,
cdf
,
quantileForecast
,
modelParameters
data(prcpTest) labels <- c("CENT","AVN","CMCG","ETA","GASP","JMA","NGPS","TCWB","UKMO") prcpTestData <- ensembleData( forecasts = prcpTest[ ,labels], dates = prcpTest$date, observations = prcpTest$obs) DATE <- sort(unique(prcpTestData$dates))[27] trainDat <- trainingData(prcpTestData, date = DATE, trainingRule = list(length=25,lag=2)) ## Not run: prcpFit <- fitBMA(trainDat, model = "gamma0") ## End(Not run) prcpFit <- fitBMAgamma0(trainDat)