Skip to main content
Log in

On the calculation of minimum variance estimators for unobservable dependent variables

  • Published:
Computational Optimization and Applications Aims and scope Submit manuscript

Abstract

The determination of minimum variance estimators in an unusual context is considered. The problem arises from an attempt to perform a regression with an unobservable dependent variable. The required minimum variance estimator is shown to satisfy a linear system of equations where the coefficient matrix has a simple structure. Uniqueness of the estimator is established by determining necessary and sufficient conditions on the data which guarantee positive definiteness of this coefficient matrix. Numerical aspects of the method of computation are also briefly explored.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. G.H. Golub and C.F. van Loan,Matrix Computations, 2nd Ed., Johns Hopkins University Press: Baltimore, MD, 1989.

    Google Scholar 

  2. J.R. Magnus and H. Neudecker,Matrix Differential Calculus with Applications in Statistics and Econometrics, Wiley: New York, NY, 1988.

    Google Scholar 

  3. G. Strang,Linear Algebra and its Applications, 3rd Ed., Harcourt, Brace, Jovanavich: San Diego, CA, 1988.

    Google Scholar 

  4. K. Wignall, private communication.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Coope, I.D. On the calculation of minimum variance estimators for unobservable dependent variables. Comput Optim Applic 2, 337–341 (1993). https://doi.org/10.1007/BF01299545

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01299545

Keywords

Navigation