## Conditions for the consistency of the total least squares estimator in an errors-in-variables linear regression model.(English. Russian original)Zbl 1328.62345

Theory Probab. Math. Stat. 83, 175-190 (2011); translation from Teor. Jmovirn. Mat. Stat. 83, 148-162 (2010).
Summary: A homoscedastic errors-in-variables linear regression model is considered. The total least squares estimator is studied. New conditions for the consistency and strong consistency of the total least squares estimator are proposed. These conditions are weaker than those proposed by A. Kukush and S. Van Huffel [Metrika 59, No. 1, 75–97 (2004; Zbl 1062.62100)].

### MSC:

 62H12 Estimation in multivariate analysis 62J05 Linear regression; mixed models 62F10 Point estimation 62F12 Asymptotic properties of parametric estimators 62J10 Analysis of variance and covariance (ANOVA)

Zbl 1062.62100
Full Text:

### References:

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