Skip to main content
SpringerLink
Log in

Comparison of Minimum Cross-Entropy Inference with Minimally Informative Information Systems

  • Chapter
Maximum-Entropy and Bayesian Methods in Science and Engineering

Part of the book series: Fundamental Theories of Physics ((FTPH,volume 31-32))

  • 676 Accesses

Abstract

The Minimum Cross-Entropy (MXE) inference rule leads to information systems which are inconsistent, and which may have an expectation less than the prior. The Min-Score rule (a generalization of maximum entropy) applied to information systems generates consistent systems and has a guaranteed expectation at least as great as the prior. The guaranteed expectation for the Min-Score rule is always at least as great as that for MXE.

Research supported in part by National Science Foundation grant IST 84-05161

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

Access this chapter

Log in via an institution
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

  • Dalkey, N. C. (1983). Updating Inductive Inference, presented at the third Workshop on Maximum Entropy and Bayesian Methods in Applied Statistics, University of Wyoming, August 1–4.

    Google Scholar 

  • Dalkey, N. C. (1985). Inductive Inference and the Maximum Entropy Principle. In Maximum Entropy and Bayesian Methods in Inverse Problems, eds. C. Ray Smith and W. T. Grandy, pp. 351–64. Dordrect/Boston/Lancaster: D. Reidel.

    Google Scholar 

  • Dalkey, N. C. (1986). Prior Probabilities Revisited. In Maximum Entropy and Bayesian Methods in Applied Statistics, ed. J. H. Justice, pp. 117–30. Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Shore, J. E. & Johnson, R. W. (1981) Properties of Cross-Entropy Minimization. IEEE Transactions on Information Theory, IT-27, 472–82.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Computer Science, UCLA, USA

    N. C. Dalkey

Authors
  1. N. C. Dalkey
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Seattle University, Seattle, Washington, USA

    Gary J. Erickson

  2. Advanced Sensors Directorate Research, Development and Engineering Center, US Army Missile Command, Redstone Arsenal, Alabama, USA

    C. Ray Smith

Rights and permissions

Reprints and permissions

Copyright information

© 1988 Kluwer Academic Publishers

About this chapter

Cite this chapter

Dalkey, N.C. (1988). Comparison of Minimum Cross-Entropy Inference with Minimally Informative Information Systems. In: Erickson, G.J., Smith, C.R. (eds) Maximum-Entropy and Bayesian Methods in Science and Engineering. Fundamental Theories of Physics, vol 31-32. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3049-0_18

Download citation

  • DOI: https://doi.org/10.1007/978-94-009-3049-0_18

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-7871-9

  • Online ISBN: 978-94-009-3049-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation