Skip to main content

Abstract

This paper is concerned with Fourier procedures in inference which admit arbitrarily high asymptotic efficiency. The problem of estimation for the stable laws is treated by two different approaches. The first involves FFT inversion of the characteristic function. A detailed discussion is given of truncation and discretization effects with reference to the special structure of the stable densities. Some further results are give also concerning a second approach based on the empirical characteristic function (ecf). Finally we sketch an application of this method to testing for independence, and also present a stationary version of the ecf.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Feuerverger, A. and Mcdunnough, P. (1981). On the efficiency of errpirical characteristic function procedures. J. Royal Statist. Soc. B, 43, to appear.

    Google Scholar 

  2. Feuerverger, A. and Mcdunnough, P. (1981). On sane Fourier rrethods for inference. J. Airrer. Statist. Assoc., Vol. 76, June, to appear.

    Google Scholar 

  3. Feuerverger, A. and Mcdunnough, P. (1981). On efficient inference in syrrrretric stable laws and processes. Proceedings of the International Symporium on statiscs and Related Topics, Ottawa, May 1980. Eds. Saleh, A.K. Md E., et. al. North Holland Publishing CO.

    Google Scholar 

  4. Dumouchel., W. H. (1973). On the asyrrptotic nornality of maximum likelihood estinates when sarrpling fran a stable distribution. Annals of Statist. 1, 948–957.

    Article  MathSciNet  Google Scholar 

  5. J Dumouchel, W. H. (1971) Stable distributions in statistical inference, Ph.D. dissertation, Yale University.

    Google Scholar 

  6. Dumouchel, W. H. (1975). Stable distributions in statistical inference: 2 – Infornation fran stably distributed sanples, J. Amer. Statist. Assoc. 70, 386–393.

    Article  MathSciNet  MATH  Google Scholar 

  7. David, H. A. (1970). Order statistics. Wiley, New York.

    MATH  Google Scholar 

  8. Parzen, E. (1979). Nonpararretric statistical data modelling. J. Amer. Statist Assoc., Vol. 74, 105–121.

    Article  MathSciNet  MATH  Google Scholar 

  9. Fenech, A. P. (1976). Asyllptotica11y efficient estimation of location for a synnetric stable law. Annals Statist. 4, 1088 1100.

    MathSciNet  Google Scholar 

  10. De Haan, L. and Resnick, S. I. (1980). A simple asynptotic estimate for the index of a stable distribution. J. Royal Statist. Soc. B, 42, 83–87.

    MathSciNet  Google Scholar 

  11. Fraser, D.A.S. (1979). Inference and linear models, McGraw Hill, New York.

    MATH  Google Scholar 

  12. Davies, R. B. (1973). Numerical inversion of a characteristic function. Biormetrika, 60, 415–417.

    Article  MATH  Google Scholar 

  13. Bohman, H. (1960). Approximate Fourier analysis of distribution functions. Ark. Mat. 4, 99–157.

    Article  MathSciNet  Google Scholar 

  14. Lukacs, E. (1970). Characteristic functions, 2nd ed., Hafner, New York.

    MATH  Google Scholar 

  15. Dumouchel, W. H. (1974). Stable distributions in statistical inference: 3 – Estimation of the parameter of a stable distribution by the nethod of maxinrum likelihood. Unpublished report. Presented to NBER-NSF Conference on Bayesian Econaretrics, Ann Arbor, April 1974.

    Google Scholar 

  16. Kendall, D. G. (1977). Hunting Quanta. 2nd ed. Proc. Symp.to Honour Jerzy neyman, Warszawa, 1974, Polish Acad. Sci., 111–159.

    Google Scholar 

  17. Wold, H.O.A. (1948). On prediction in stationary tine series. Annals Math. Statist. 19, 558–567.

    Article  MathSciNet  MATH  Google Scholar 

  18. Feuerverger, A. and Mureika, R.A. (1977). The empirica1 characteristic function and its applications. Annals Statist. 5, 88–97.

    Article  MathSciNet  MATH  Google Scholar 

  19. Csorgo, S. (1981). Limit behaviour of the empirica1 characteristic flmction. Annals Probab., to appear.

    Google Scholar 

  20. Kent, T. J. (1975). A weak convergence theorem for the errpirica1 characteristic function. J. Appl. Probab. 12, 515–523.

    Article  MathSciNet  MATH  Google Scholar 

  21. Bohr, H. A. (1947).Almost periodic functions, chelssea, Chelsea, New York.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1981 Springer-Verlag New York Inc.

About this paper

Cite this paper

Feuerverger, A., McDunnough, P. (1981). Efficient Estimation for the Stable Laws. In: Eddy, W.F. (eds) Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-9464-8_9

Download citation

  • DOI: https://doi.org/10.1007/978-1-4613-9464-8_9

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-90633-1

  • Online ISBN: 978-1-4613-9464-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics