Journal of Statistical Physics

, Volume 26, Issue 4, pp 807–815 | Cite as

The maximum entropy principle as a consequence of the principle of Laplace

  • N. Hadjisavvas


The maximum entropy principle states that the probability distribution which best represents our information is the one which maximizes the entropy with the given evidence as constraints. We prove that this principle is implied from the Laplace principle of equiprobabilities applied to the setS of allN-term sequences of results which are compatible with the given evidence. We generalize to the “information gain” method of Kullback.

Key words

Maximum entropy “Jaynes” statistical inference 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    E. T. Jaynes,Phys. Rev. 106:620 (1957);108:171 (1957).Google Scholar
  2. 2.
    E. T. Jaynes, inColloquium Lectures in Pure and Applied Science, No. 4 (February 1958).Google Scholar
  3. 3.
    J. Cyranski,Found. Phys. 8(5/6):493 (1978).Google Scholar
  4. 4.
    K. Friedman and A. Shimony,J. Stat. Phys. 3:381 (1971).Google Scholar
  5. 5.
    E. T. Jaynes,I.E.E.E. Trans. Syst. Scien. Cyb. SSC-4:227 (1968).Google Scholar
  6. 6.
    E. T. Jaynes, inStatistical Physics, Vol. 3, K. W. Ford, ed. (W. A. Benjamin, New York, 1963).Google Scholar
  7. 7.
    S. Kullback,Information Theory and Statistics (Wiley, New York, 1959).Google Scholar
  8. 8.
    M. Mugur-Schächter,Ann. Inst. Henri Poincaré A 32(1):33 (1980).Google Scholar

Copyright information

© Plenum Publishing Corporation 1981

Authors and Affiliations

  • N. Hadjisavvas
    • 1
  1. 1.Laboratoire de Mécanique QuantiqueReimsFrance

Personalised recommendations