scholarly journals Consistency of the total least squares estimator in the linear errors-in-variables regression

2018 ◽  
Vol 5 (3) ◽  
pp. 247-295
Author(s):  
Sergiy Shklyar
Keyword(s):  
Least Squares ◽  
Total Least Squares ◽  
Least Squares Estimator ◽  
Errors In Variables

Bootstrapped Total Least Squares estimator using (circular) overlap for Errors-In-Variables identification

2009 ◽  
Vol 42 (10) ◽  
pp. 1568-1573
Author(s):  
Gerd Vandersteen ◽  
Kurt Barbé ◽  
Rik Pintelon ◽  
Johan Schoukens
Keyword(s):  
Least Squares ◽  
Total Least Squares ◽  
Least Squares Estimator ◽  
Errors In Variables

scholarly journals Modifying Cadzow's algorithm to generate the optimal TLS-solution for the structured EIV-Model of a similarity transformation

2012 ◽  
Vol 2 (2) ◽  
pp. 98-106 ◽  
Author(s):  
B. Schaffrin ◽  
F. Neitzel ◽  
S. Uzun ◽  
V. Mahboub
Keyword(s):  
Least Squares ◽  
Similarity Transformation ◽  
Optimal Solution ◽  
Total Least Squares ◽  
Errors In Variables ◽  
Parameter Adjustment ◽  
Structured Errors

Modifying Cadzow's algorithm to generate the optimal TLS-solution for the structured EIV-Model of a similarity transformationIn 2005, Felus and Schaffrin discussed the problem of a Structured Errors-in-Variables (EIV) Model in the context of a parameter adjustment for a classical similarity transformation. Their proposal, however, to perform a Total Least-Squares (TLS) adjustment, followed by a Cadzow step to imprint the proper structure, would not always guarantee the identity of this solution with the optimal Structured TLS solution, particularly in view of the residuals. Here, an attempt will be made to modify the Cadzow step in order to generate the optimal solution with the desired structure as it would, for instance, also result from a traditional LS-adjustment within an iteratively linearized Gauss-Helmert Model (GHM). Incidentally, this solution coincides with the (properly) Weighted TLS solution which does not need a Cadzow step.

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