Entropy and Divergence Associated with Power Function and the Statistical Application

نویسندگان

  • Shinto Eguchi
  • Shogo Kato
چکیده

In statistical physics, Boltzmann-Shannon entropy provides good understanding for the equilibrium states of a number of phenomena. In statistics, the entropy corresponds to the maximum likelihood method, in which Kullback-Leibler divergence connects Boltzmann-Shannon entropy and the expected log-likelihood function. The maximum likelihood estimation has been supported for the optimal performance, which is known to be easily broken down in the presence of a small degree of model uncertainty. To deal with this problem, a new statistical method, closely related to Tsallis entropy, is proposed and shown to be robust for outliers, and we discuss a local learning property associated with the method.

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عنوان ژورنال:
  • Entropy

دوره 12  شماره 

صفحات  -

تاریخ انتشار 2010