• DocumentCode
    3050634
  • Title

    Asymptotic minimax regret for data compression, gambling and prediction

  • Author

    Xie, Qun ; Barron, Andrew R.

  • Author_Institution
    Dept. of Stat., Yale Univ., New Haven, CT, USA
  • fYear
    1997
  • fDate
    29 Jun-4 Jul 1997
  • Firstpage
    315
  • Abstract
    The asymptotic minimax regret rn=minqmaxxn(log 1/q(xn)-log 1/p(xn|θˆ)) for the target family of memoryless sources on a given alphabet equals ((m-1)/2)logn+Cm+o(1). We determine the optimal constant Cm and we show that a slight modification of the Dirichlet (1/2, ..., 1/2) mixture is asymptotically minimax
  • Keywords
    data compression; encoding; game theory; minimax techniques; prediction theory; alphabet; asymptotic minimax regret; asymptotically minimax Dirichlet mixture; data compression; gambling; game theory; maximum likelihood estimator; memoryless sources; optimal constant; prediction; Data compression; Frequency; Indexing; Loss measurement; Maximum likelihood estimation; Minimax techniques; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
  • Conference_Location
    Ulm
  • Print_ISBN
    0-7803-3956-8
  • Type

    conf

  • DOI
    10.1109/ISIT.1997.613240
  • Filename
    613240
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3050634