\name{forecastCovEstimatorsWRTtrue}
\alias{forecastCovEstimatorsWRTtrue}
\alias{is.forecastCovEstimatorsWRTtrue}

\title{Compare Forecasts Cov Relative to True Model Output}
\description{Compare covariance of the forecasts less the true model output}
\usage{
    forecastCovEstimatorsWRTtrue(true.model, rng=NULL,
                       simulation.args=NULL,
                       est.replications = 2, pred.replications = 2,
                       discard.before = 10, horizons = 1:12, quiet =FALSE,
                       estimation.methods=NULL, compiled=.DSEflags()$COMPILED) 
%%                       Spawn=if (exists(".SPAWN")) .SPAWN else FALSE
    is.forecastCovEstimatorsWRTtrue(obj)
}
\arguments{
    \item{true.model}{An object of class TSmodel.}
    \item{estimation.methods}{A list as used by estimateModels.}
    \item{simulation.args}{an arguments to be passed to simulate.}
    \item{est.replications}{An arguments to be passed to simulate.}
    \item{pred.replications}{An arguments to be passed to simulate.}
    \item{discard.before}{
      An integer indicating the number of points in the
      beginning of forecasts to discard for calculating covariances.}
    \item{horizons}{Horizons for which forecast covariance should be calculated.}
    \item{rng}{If specified then it is used to set RNG.}
%%    \item{Spawn}{If TRUE then Splus For loops are used.}
    \item{quiet}{If TRUE then some messages are not printed.}
    \item{compiled}{a logical indicating if the compiled version of the code
       should be used. (FALSE would typically only be used for debugging.)}
    \item{obj}{an object.}
}
\value{
The returned results has element
  \code{forecastCov.true, forecastCov.zero, forecastCov.trend} containing 
     covariances averaged over estimation replications and simulation
     replications (forecasts will not change but simulated data will).
   \code{forecastCov} a list of the same length as estimation.methods with each
     element containing covariances averaged over estimation replications 
     and simulation replications.
   \code{estimatedModels} a list of length est.replications, with each elements as
     returned by estimateModels, thus each element has \code{multi.model} as a
     subelement containing models for different estimation techniques.  
     So, eg. \code{estimatedModels[[2]]$multi.model[[1]]}  in the result will
     be the model from the first estimation technique in the second replication.
}
\details{
Calculate the forecasts cov of models estimated from simulations of 
  true.model with estimation methods indicated by estimation.methods (see 
       estimateModels). 
This function makes multiple calls to forecastCovWRTtrue.
}
\seealso{
\code{\link{forecastCovWRTtrue}}
\code{\link{forecastCovEstimatorsWRTdata}}
}
\examples{
data("eg1.DSE.data.diff", package="dse")
true.model <- estVARXls(eg1.DSE.data.diff) # just to have a starting model
z <-  forecastCovEstimatorsWRTtrue(true.model, 
    estimation.methods=list(estVARXls=list(max.lag=4)))
}
\concept{DSE}
\keyword{ts}