https://github.com/cran/dse
Tip revision: f9aa6f7ec42024ca88a37a5e6984bada0a8d3891 authored by Paul Gilbert on 07 March 2013, 08:03:12 UTC
version 2013.3-2
version 2013.3-2
Tip revision: f9aa6f7
toSSChol.Rd
\name{toSSChol}
\alias{toSSChol}
\alias{toSSChol.TSmodel}
\alias{toSSChol.TSestModel}
\title{Convert to Non-Innovation State Space Model}
\description{
This function may not be working properly.
Convert to a non-innovations state space representation using
the given matrix (Om) as the measurement noise covariance.
Om would typically be an estimate of the output noise, such as returned
in \code{$estimates$cov} of the function \code{l} (\code{l.SS} or \code{l.ARMA}).
This assumes that the noise processes in the arbitrary SS representation
are white and uncorrelated.
}
\usage{
toSSChol(model, ...)
\method{toSSChol}{TSmodel}(model, Om=diag(1,nseriesOutput(model)), ...)
\method{toSSChol}{TSestModel}(model, Om=NULL, ...)
}
\arguments{
\item{model}{An object of class TSmodel.}
\item{Om}{
a matrix to be used as the measurement noise covariance. If Om is
not supplied and model is of class TSestModel then
\code{model$estimates$cov} is used. Otherwise, Om is set to the
identity matrix.}
\item{...}{arguments to be passed to other methods.}
}
\value{
An object of class 'SS' 'TSmodel' containing a state space model which is
not in innovations form.
}
\details{
Convert to a non-innovations SS representation using a Cholesky
decomposition of Om as the coefficient matrix of the output noise.
}
\seealso{
\code{\link{toSSinnov}}
}
\examples{
data("eg1.DSE.data.diff", package="dse")
model <- estVARXls(eg1.DSE.data.diff)
model <- toSSChol(model)
}
\concept{DSE}
\keyword{ts}