@TechReport{	  it:2009-016,
  author	= {Torsten S{\"o}derstr{\"o}m},
  title		= {Expressions for the Covariance Matrix of Covariance Data},
  institution	= {Department of Information Technology, Uppsala University},
  department	= {Division of Systems and Control},
  year		= {2009},
  number	= {2009-016},
  month		= may,
  abstract	= {In several estimation methods used in system
		  identification, a first step is to estimate the covariance
		  functions of the measured inputs and outputs for a small
		  set of lags. These covariance elements can be set up as a
		  vector. The report treats the problem of deriving and
		  computing the asymptotic covariance matrix of this vector,
		  when the number of underlying input-output data is large.
		  The derived algorithm is derived under fairly general
		  assumptions. It is assumed that the input and output are
		  linked through a linear finite-order system. Further, the
		  input is assumed to be modelled as an ARMA model of a
		  fixed, but arbitrary order. Finally, it is allowed that the
		  both the input and the output are not measured directly,
		  but with some white measurement noise, thus including
		  typical errors-in-variables situations in the analysis.}
}