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Comparative Study of Different Penalty Functions and Algorithms in Survey Calibration

  • Gareth DaviesEmail author
  • Jonathan Gillard
  • Anatoly Zhigljavsky
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 107)

Abstract

The technique of calibration in survey sampling is a widely used technique in the field of official statistics. The main element of the calibration process is an optimization procedure, for which a variety of penalty functions can be used. In this chapter, we consider three of the classical penalty functions that are implemented in many of the standard calibration software packages. We present two algorithms used by many of these software packages, and explore the properties of the calibrated weights and the corresponding estimates when using these two algorithms with the classical calibration penalty functions.

Keywords

Survey calibration Optimization g-Weights 

Notes

Acknowledgements

Work of the first author was supported by the Engineering and Physical Sciences Research Council, project number 1638853 “Examination of approaches to calibration and weighting for non-response in cross-sectional and longitudinal surveys.” The work of the third author was supported by the Russian Science Foundation, project No. 15-11-30022 “Global optimization, supercomputing computations, and application”.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Gareth Davies
    • 1
    Email author
  • Jonathan Gillard
    • 1
  • Anatoly Zhigljavsky
    • 1
  1. 1.Cardiff School of MathematicsCardiff UniversityCardiffUK

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