Generalized Non-extensive Statistical Distributions
Oscar Sotolongo-Costa, Alejandro Gonzalez Gonzalez, Francois Brouers
Abstract
We find the value of constants related to constraints in characterization of some known statistical distributions and then we proceed to use the idea behind maximum entropy principle to derive generalized version of this distributions using the Tsallis' and Renyi information measures instead of the well-known Bolztmann-Gibbs-Shannon. These generalized distributions will depend on q (real number) and in the limit (q=1) we obtain the "classical" ones. We found that apart from a constant, generalized versions of statistical distributions following Tsallis' or Renyi are undistinguishable.
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