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The L-decomposable and the bi-decomposable models are two families of distributions on the set of all permutations of the first positive integers. Both of these models are characterized by collections of conditional independence relations. We first compute a Markov basis for the L-decomposable model, then give partial results about the Markov basis of the bi-decomposable model. Using these Markov bases, we show that not all bi-decomposable distributions can be approximated arbitrarily well by...
MSC 2010: 15A15, 15A52, 33C60, 33E12, 44A20, 62E15 Dedicated to Professor R. Gorenflo on the occasion of his 80th birthdayA connection between fractional calculus and statistical distribution
theory has been established by the authors recently. Some extensions of
the results to matrix-variate functions were also considered. In the present
article, more results on matrix-variate statistical densities and their connections to fractional calculus will be established. When considering solutions of fractional...
The problem to maximize the information divergence from an exponential family is generalized to the setting of Bregman divergences and suitably defined Bregman families.
En este trabajo estudiamos la asociación entre dos variables aleatorias discretas (no cardinales) definiendo una nueva medida [de] asociación, la cual está basada en la velocidad de convergencia del vector de probabilidad correspondiente a la cadena de Markov asociada a la distribución de probabilidad conjunta de las variables en estudio. Ponemos especial énfasis en el estudio muestral y propiedades de los estimadores de dicha medida, calculando sus distribuciones asintóticas bajo el muestreo multinomial...
Disparities of discrete distributions are introduced as a natural and useful extension of the information-theoretic divergences. The minimum disparity point estimators are studied in regular discrete models with i.i.d. observations and their asymptotic efficiency of the first order, in the sense of Rao, is proved. These estimators are applied to continuous models with i.i.d. observations when the observation space is quantized by fixed points, or at random, by the sample quantiles of fixed orders....
A misclassified size-biased modified power series distribution (MSBMPSD) where some of the observations corresponding to are misclassified as with probability , is defined. We obtain its recurrence relations among ordinary, central and factorial moments and also for some of its particular cases like the size-biased generalized negative binomial (SBGNB) and the size-biased generalized Poisson (SBGP) distributions. We also discuss the effect of the misclassification on the variance for MSBMPSD...
We study the problem of finding the smallest such that every element of an exponential family can be written as a mixture of elements of another exponential family. We propose an approach based on coverings and packings of the face lattice of the corresponding convex support polytopes and results from coding theory. We show that is the smallest number for which any distribution of
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