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( h , Φ ) -entropy differential metric

María Luisa Menéndez, Domingo Morales, Leandro Pardo, Miquel Salicrú (1997)

Applications of Mathematics

Burbea and Rao (1982a, 1982b) gave some general methods for constructing quadratic differential metrics on probability spaces. Using these methods, they obtained the Fisher information metric as a particular case. In this paper we apply the method based on entropy measures to obtain a Riemannian metric based on ( h , Φ ) -entropy measures (Salicrú et al., 1993). The geodesic distances based on that information metric have been computed for a number of parametric families of distributions. The use of geodesic...

( R , S ) -information radius of type t and comparison of experiments

Inder Jeet Taneja, Luis Pardo, D. Morales (1991)

Applications of Mathematics

Various information, divergence and distance measures have been used by researchers to compare experiments using classical approaches such as those of Blackwell, Bayesian ets. Blackwell's [1] idea of comparing two statistical experiments is based on the existence of stochastic transformations. Using this idea of Blackwell, as well as the classical bayesian approach, we have compared statistical experiments by considering unified scalar parametric generalizations of Jensen difference divergence measure....

A general class of entropy statistics

María Dolores Esteban (1997)

Applications of Mathematics

To study the asymptotic properties of entropy estimates, we use a unified expression, called the H h , v ϕ 1 , ϕ 2 -entropy. Asymptotic distributions for these statistics are given in several cases when maximum likelihood estimators are considered, so they can be used to construct confidence intervals and to test statistical hypotheses based on one or more samples. These results can also be applied to multinomial populations.

A geometry on the space of probabilities (I). The finite dimensional case.

Henryk Gzyl, Lázaro Recht (2006)

Revista Matemática Iberoamericana

In this note we provide a natural way of defining exponential coordinates on the class of probabilities on the set Ω = [1,n] or on P = {p = (p1, ..., pn) ∈ Rn| pi > 0; Σi=1n pi = 1}. For that we have to regard P as a projective space and the exponential coordinates will be related to geodesic flows in Cn.

A geometry on the space of probabilities (II). Projective spaces and exponential families.

Henryk Gzyl, Lázaro Recht (2006)

Revista Matemática Iberoamericana

In this note we continue a theme taken up in part I, see [Gzyl and Recht: The geometry on the class of probabilities (I). The finite dimensional case. Rev. Mat. Iberoamericana 22 (2006), 545-558], namely to provide a geometric interpretation of exponential families as end points of geodesics of a non-metric connection in a function space. For that we characterize the space of probability densities as a projective space in the class of strictly positive functions, and these will be regarded as a...

A log-Sobolev type inequality for free entropy of two projections

Fumio Hiai, Yoshimichi Ueda (2009)

Annales de l'I.H.P. Probabilités et statistiques

We prove a kind of logarithmic Sobolev inequality claiming that the mutual free Fisher information dominates the microstate free entropy adapted to projections in the case of two projections.

A new approach to mutual information

Fumio Hiai, Dénes Petz (2007)

Banach Center Publications

A new expression as a certain asymptotic limit via "discrete micro-states" of permutations is provided for the mutual information of both continuous and discrete random variables.

A new approach to mutual information. II

Fumio Hiai, Takuho Miyamoto (2010)

Banach Center Publications

A new concept of mutual pressure is introduced for potential functions on both continuous and discrete compound spaces via discrete micro-states of permutations, and its relations with the usual pressure and the mutual information are established. This paper is a continuation of the paper of Hiai and Petz in Banach Center Publications, Vol. 78.

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