• DocumentCode
    1779868
  • Title

    Information geometry approach to parameter estimation in Markov chains

  • Author

    Hayashi, Mariko ; Watanabe, Shigetaka

  • Author_Institution
    Grad. Sch. of Math., Nagoya Univ., Nagoya, Japan
  • fYear
    2014
  • fDate
    June 29 2014-July 4 2014
  • Firstpage
    1091
  • Lastpage
    1095
  • Abstract
    We consider the parameter estimation of Markov chain when the unknown transition matrix belongs to an exponential family of transition matrices. Then, we show that the sample mean of the generator of the exponential family is an asymptotically efficient estimator. Further, we also define a curved exponential family of transition matrices. Using a transition matrix version of the Pythagorean theorem, we give an asymptotically efficient estimator for a curved exponential family.
  • Keywords
    Markov processes; information theory; matrix algebra; Markov chains; Pythagorean theorem; asymptotically efficient estimator; curved exponential family; information geometry approach; parameter estimation; unknown transition matrix; Educational institutions; Entropy; Generators; Information geometry; Information theory; Markov processes; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory (ISIT), 2014 IEEE International Symposium on
  • Conference_Location
    Honolulu, HI
  • Type

    conf

  • DOI
    10.1109/ISIT.2014.6875001
  • Filename
    6875001