@TechReport{	  it:2008-008,
  author	= {Mei Hong and Torsten S{\"o}derstr{\"o}m},
  title		= {Relations between Bias-Eliminating Least Squares, the
		  {F}risch Scheme and Extended Compensated Least Squares
		  Methods for Identifying Errors-in-Variables Systems},
  institution	= {Department of Information Technology, Uppsala University},
  department	= {Division of Systems and Control},
  year		= {2008},
  number	= {2008-008},
  month		= mar,
  abstract	= {There are many methods for identifying errors-in-variables
		  systems. Among them Bias-Eliminating Least Squares (BELS),
		  the Frisch scheme and Extended Compensated Least Squares
		  (ECLS) methods are attractive approaches because of their
		  simplicity and good estimation accuracy. These three
		  methods are all based on a bias-compensated least-squares
		  (BCLS) principle. In this report, the relations between
		  them are considered. In particular, the nonlinear equations
		  utilized in these three methods are proved to be equivalent
		  under different noise conditions. It is shown that BELS,
		  Frisch and ECLS methods have the same asymptotic estimation
		  accuracy providing the same extended vector is used.}
}