Skip to main content

Abstract

The main aim of this paper is to help to clarify the situation which occurs in time series design problems when an infinite-dimensional regression experiment is to be performed. The notion of an approximate estimability of a functional defined on the space of regression functions, which arises in the case of an infinite-dimensional regression experiment, is discussed here (Theorem 2). Theorem 3 gives a condition under which designs optimal for finite-dimensional regression problems may be considered as approximately optimal also in the infinite-dimensional case. In section 3 some remarks about the possibility of comparing two designs with uncorrelated observations are given.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. N. Aronszajn: Theory of reproducing kernels. Trans. Amer. Math. Soc. 68 (1950), 337–404.

    Article  MathSciNet  MATH  Google Scholar 

  2. C. L. Atwood: Sequences converging to D-optimal designs of experiments. Ann. of Statist. 1 (1973), 2, 342–352.

    Article  MathSciNet  Google Scholar 

  3. V. V. Fedorov, A. Pázman: Design of Physical Experiments (Statistical methods). Fortschritted. Physik 16 (1968), 325–355.

    Google Scholar 

  4. P. R. Halmos: Introduction to Hilbert space. Chelsea, New York 1957.

    MATH  Google Scholar 

  5. S. Karlin, W. J. Studden: Optimal experimental designs. Ann. Math. Statist. 39 (1966), 4, 783–815.

    Article  MathSciNet  Google Scholar 

  6. J. Kiefer, J. Wolfowitz: Optimum designs in regression problems. Ann. Math. Statist. 50(1959), 271–294.

    Article  MathSciNet  Google Scholar 

  7. E. Parsen: Regression analysis of continuous parameter time series. In: Proc. Fourth Berkeley Symp. Math. Statist. Prob., 1961. Univ. of California, Berkeley, 1963, 469–490.

    Google Scholar 

  8. A. Pázman: The ordering of experimental designs. A Hilbert space approach. Kybernetika (1974) (to appear).

    Google Scholar 

  9. J. A. Rozanov: Gaussovskije beskonečnomernyje raspredelenija. Nauka, Moskva 1968.

    Google Scholar 

  10. J. Sacks, D. Ylvisaker: Designs for regression problems with correlated errors. Ann, Math. Statist. 37 (1966), 1, 66–89.

    Article  MathSciNet  MATH  Google Scholar 

  11. J. Sacks, D. Ylvisaker: Designs for regression problems with correlated errors; many parameters. Ann. Math. Statist. 39 (1968), 1, 49–69.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

J. Kožešnik

Rights and permissions

Reprints and permissions

Copyright information

© 1977 ACADEMIA, Publishing House of the Czechoslovak Academy of Sciences, Prague

About this chapter

Cite this chapter

Pázman, A. (1977). A Contribution to the Time Series Design Problems. In: Kožešnik, J. (eds) Transactions of the Seventh Prague Conference on Information Theory, Statistical Decision Functions, Random Processes and of the 1974 European Meeting of Statisticians. Transactions of the Seventh Prague Conference on Information Theory, Statistical Decision Functions, Random Processes and of the 1974 European Meeting of Statisticians, vol 7A. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-9910-3_47

Download citation

  • DOI: https://doi.org/10.1007/978-94-010-9910-3_47

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-9912-7

  • Online ISBN: 978-94-010-9910-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics