, Volume 64, Issue 1, pp 41–46 | Cite as

Non-Existence of the First Moment of the Adjusted Least Squares Estimator in Multivariate Errors-in-Variables Model

Original Article


The linear normal multivariate errors-in-variables model is considered. The model involves an equation error. It is proved in both structural and functional cases that the first moment of the adjusted least squares estimator does not exist.


Adjusted least squares Equation error model Functional model Infinite first moment Linear multivariate error-in-variables model Structural model 

AMS Subject Classifications

62J05 62H12 62H10 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Cheng CL, Van Ness JW (1999) Statistical regression with measurement error. Arnold, LondonMATHGoogle Scholar
  2. Cheng CL, Schneeweiss H, Thamerus M (2000) A small sample estimator for a polynomial regression with errors in the variables. J Roy Stat Soc B 62:699–709CrossRefMATHMathSciNetGoogle Scholar
  3. Fuller WA (1987) Measurement error models. Wiley, New YorkMATHGoogle Scholar
  4. Gleser LJ (1992) The importance of assessing measurement reliability in multivariate regression. J Am Stat Assoc 87:696–707MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Institute of Statistical ScienceAcademia SinicaTaipeiRepublic of China
  2. 2.Department of Mechanics and MathematicsNational Taras Shevchenko UniversityKievUkraine

Personalised recommendations