[go: up one dir, main page]

Skip to main content
Log in

An interval method for bounding level sets of parameter estimation problems

Ein Intervallverfahren für die Beschränkung der Niveaumengen von Parameterschätzungsaufgaben

  • Published:
Computing Aims and scope Submit manuscript

Abstract

A new method is presented using inclusive functions and interval arithmetic for bounding the level sets of nonlinear parameter estimation problems with objective function of sum-of-squares type. The result box bounding a level set conveys more information for the user than the usual local minimum points do. The rate of convergence is in general linear, in special cases it can be superlinear or higher. The condition of convergence is studied, and examples are shown.

Zusammenfassung

Es wird eine neue Methode vorgestellt für die Beschränkung der Niveaumengen von nichtlinearen Parameterschätzungsaufgaben mit Zielfunktion von Quadratsummen-Form unter Verwendung von Inklusionsfunktionen und Intervallarithmetik. Die Ergebnismenge, die eine Niveaumenge beschränkt, bietet mehr Informationen für den Benutzer als die üblichen lokalen Minimum-Punkte. Die Konvergenzgeschwindigkeit ist im allgemeinen linear, in Spezialfällen kann sie superlinear oder höher sein. Die Konvergenzbedingungen werden untersucht und Beispiele gezeigt.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Bleher, J. H., Rump, S. M., Kulisch, U., Metzger, M., Ullrich, Ch., Walter, W.: FORTRAN-SC. A study of a FORTRAN extension for engineering/scientific computation with access to ACRITH. Computing39, 93–110 (1987).

    Google Scholar 

  2. Csendes, T., Daróczy, B., Hantos, Z.: Nonlinear parameter estimation by global optimization: comparison of local search methods in respiratory system modelling. In: System Modelling and Optimization (A. Prékopa, J. Szelezsán, B. Strazicky, eds.), pp. 188–192. New York-Berlin-Heidelberg: Springer 1986.

    Google Scholar 

  3. Csendes, T.: Nonlinear parameter estimation by global optimization — efficiency and reliability. Acta Cybernetica (to appear).

  4. Gill, P. E., Murray, W., Wright, M. H.: Practical Optimization. London: Academic Press 1981.

    Google Scholar 

  5. Hantos, Z., Daróczy, B., Suki, B., Galgóczy, G., Csendes, T.: Forced oscillatory impedance of the respiratory system at low frequencies. J. of Applied Physiology60, 123–132 (1986).

    Google Scholar 

  6. Krawczyk, R.: Properties of interval operators. Computing37, 227–245 (1986).

    Google Scholar 

  7. Kulisch, U. (ed.): PASCAL-SC: A PASCAL Extension for Scientific Computation. Information Manual and Floppy Disks, Version IBM PC/AT, Operating System DOS, B. G. Teubner, Stuttgart. Chichester: John Wiley & Sons 1987.

    Google Scholar 

  8. Lutchen, K. R., Jackson, A. C.: Statistical measures of parameter estimates from models fit to respiratory impedance data: emphasis on joint variabilities. IEEE Trans. Biomed. Eng.BME-33, 1000–1009 (1986).

    Google Scholar 

  9. Ratschek, H., Rokne, J.: Computer Methods for the Range of Functions. Chichester: Ellis Horwood 1984.

    Google Scholar 

  10. Ratschek, H.: Inclusion functions and global optimization. Math. Programming33, 300–317 (1985).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Csendes, T. An interval method for bounding level sets of parameter estimation problems. Computing 41, 75–86 (1989). https://doi.org/10.1007/BF02238730

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02238730

AMS Subject Classifications

Key words

Navigation