The Frisch scheme in dynamic system identification
Automatica (Journal of IFAC) - Identification and system parameter estimation
Perspectives on errors-in-variables estimation for dynamic systems
Signal Processing
Survey paper: Errors-in-variables methods in system identification
Automatica (Journal of IFAC)
A covariance matching approach for identifying errors-in-variables systems
Automatica (Journal of IFAC)
Accuracy analysis of a covariance matching approach for identifying errors-in-variables systems
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Comparing some classes of bias-compensating least squares methods
Automatica (Journal of IFAC)
Hi-index | 22.15 |
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 paper, the relationships between them are considered. In particular, the set of nonlinear equations utilized in these three methods are proved to be equivalent under different noise conditions also for finite samples. It is shown that BELS, Frisch and ECLS methods have the same asymptotic estimation accuracy providing the same extended vector is used.