Displaying similar documents to “Maximizing multi–information”

Generalized probability functions.

Souto Martinez, Alexandre, Silva González, Rodrigo, Sangaletti Terçariol, César Augusto (2009)

Advances in Mathematical Physics

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On limiting towards the boundaries of exponential families

František Matúš (2015)

Kybernetika

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This work studies the standard exponential families of probability measures on Euclidean spaces that have finite supports. In such a family parameterized by means, the mean is supposed to move along a segment inside the convex support towards an endpoint on the boundary of the support. Limit behavior of several quantities related to the exponential family is described explicitly. In particular, the variance functions and information divergences are studied around the boundary. ...

Characterizations of the exponential distribution based on certain properties of its characteristic function

Simos G. Meintanis, George Iliopoulos (2003)

Kybernetika

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Two characterizations of the exponential distribution among distributions with support the nonnegative real axis are presented. The characterizations are based on certain properties of the characteristic function of the exponential random variable. Counterexamples concerning more general possible versions of the characterizations are given.

Maximizing the Bregman divergence from a Bregman family

Johannes Rauh, František Matúš (2020)

Kybernetika

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The problem to maximize the information divergence from an exponential family is generalized to the setting of Bregman divergences and suitably defined Bregman families.