• DocumentCode
    2337480
  • Title

    Jeffreys´ prior yields the asymptotic minimax redundancy

  • Author

    Clarke, Bertrand S. ; Barron, Andrew R.

  • Author_Institution
    Dept. of Stat., British Columbia Univ., Vancouver, BC, Canada
  • fYear
    1994
  • fDate
    27-29 Oct 1994
  • Firstpage
    14
  • Abstract
    We determine the asymptotic minimax redundancy of universal data compression in a parametric setting and show that it corresponds to the use of Jeffreys prior. Statistically, this formulation of the coding problem can be interpreted in a prior selection context and in an estimation context
  • Keywords
    estimation theory; minimax techniques; redundancy; source coding; statistical analysis; Jeffreys´ prior; asymptotic minimax redundancy; coding problem; estimation context; parametric setting; source coding; universal data compression; Channel coding; Data compression; Entropy; Game theory; Maximum likelihood decoding; Maximum likelihood estimation; Minimax techniques; Mutual information; Source coding; Statistical distributions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory and Statistics, 1994. Proceedings., 1994 IEEE-IMS Workshop on
  • Conference_Location
    Alexandria, VA
  • Print_ISBN
    0-7803-2761-6
  • Type

    conf

  • DOI
    10.1109/WITS.1994.513856
  • Filename
    513856
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2337480