Skip to main content
Log in

Calibration and convex programming: two approaches to one problem

  • Original Paper
  • Published:
Central European Journal of Operations Research Aims and scope Submit manuscript

Abstract

Calibration is a common technique of data processing in survey sampling. Although convex programming would be an obvious tool for this purpose, usually other methods are used in the practice of statistical institutes. A comparison of those methods and convex programming is reported on in this paper.

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

  • Cochran WG (1977) Sampling techniques. Wiley, New York, xvi+428 p

    Google Scholar 

  • Darroch JN, Ratcliff D (1972) Generalized iterative scaling for log-linear models. Ann Math Stat 43(5): 1470–1480

    Article  Google Scholar 

  • Deville J-C, Särndal C-E (1992) Calibration estimation in survey sampling. J Am Stat Assoc 87(418): 376–382

    Article  Google Scholar 

  • Deville J-C, Särndal C-E, Sautory O (1993) Generalized raking procedures in survey sampling. J Am Stat Assoc 88(423): 1013–1920

    Article  Google Scholar 

  • Neumann K (1975) Operations research Verfahren. Bd. I. Carl Hanser Verlag, München, 377 p

  • Schittkowski K (1985) LINSCH—Subroutine LP0001 (for) solving linear programming problems. Mathematisches Institut, Universität Bayreuth, Germany

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to László Mihályffy.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mihályffy, L. Calibration and convex programming: two approaches to one problem. Cent Eur J Oper Res 19, 225–238 (2011). https://doi.org/10.1007/s10100-010-0147-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10100-010-0147-6

Keywords

Navigation