Skip to main content

Part of the book series: Statistics for Industry and Technology ((SIT))

Abstract

Sufficient conditions are given under which the distribution of a finite quadratic form in independent identically distributed symmetric random variables defines uniquely the underlying distribution. Moreover, a stability theorem for quadratic forms is proved.

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
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover 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. Akhizer, N. I (1961). Classical Problem of Moments Moscow: FML.

    Google Scholar 

  2. Feller, W. (1971). An Introdution to Probability Theory and Its Applica-tions, Vol. 2, New York: John Wiley & Sons.

    Google Scholar 

  3. Khakhubiya, T. G. (1965). A lemma on random determinants and its application to the characterization of multivariate distributions, Theory of Probability and Its Applications, 10, 685–689.

    Article  Google Scholar 

  4. Linnik, Yu. V. and Ostrovski, I. V. (1972). Decomposition of Random Variables and Vectors Moscow: Nauka. English Translation in American Mathematical Society Translations, 48,(1977), Providence, Rhode Island: American Mathematical Soceity.

    Google Scholar 

  5. Lukacs, E. (1970). Characteristic Functions, Second edition, London: Griffin.

    MATH  Google Scholar 

  6. Lukacs, E. and Laha, R. G. (1964). Applications of Characteristic Functions London: Griffin.

    MATH  Google Scholar 

  7. Prohorov, Yu. (1956). Convergence of random processes and limit theorems in probability theory, Theory of Probability and Its Applications, 1, 157–214.

    Article  MathSciNet  Google Scholar 

  8. Shohat, J. A. and Tamarkin, J. D. (1970). The Problem of Moments, Providence, Rhode Island: American Mathematical Society.

    Google Scholar 

  9. Stoyanov, J. M. (1987). Counterexamples in Probability, New York: John Wiley & Sons.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer Science+Business Media New York

About this chapter

Cite this chapter

Christoph, G., Prohorov, Y., Ulyanov, V. (2001). Characterization and Stability Problems for Finite Quadratic Forms. In: Balakrishnan, N., Ibragimov, I.A., Nevzorov, V.B. (eds) Asymptotic Methods in Probability and Statistics with Applications. Statistics for Industry and Technology. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-0209-7_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4612-0209-7_3

  • Publisher Name: Birkhäuser, Boston, MA

  • Print ISBN: 978-1-4612-6663-1

  • Online ISBN: 978-1-4612-0209-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics