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Several results on set-valued possibilistic distributions

Ivan Kramosil, Milan Daniel (2015)

Kybernetika

When proposing and processing uncertainty decision-making algorithms of various kinds and purposes, we more and more often meet probability distributions ascribing non-numerical uncertainty degrees to random events. The reason is that we have to process systems of uncertainties for which the classical conditions like σ -additivity or linear ordering of values are too restrictive to define sufficiently closely the nature of uncertainty we would like to specify and process. In cases of non-numerical...

Sobre el tamaño de muestra para experimentos aleatorios con imprecisión difusa.

M.ª Angeles Gil Alvarez, Pedro Gil Alvarez (1988)

Trabajos de Estadística

Statistical Inference deals with the drawing of conclusions about a random experiment on the basis of the information contained in a sample from it. A random experiment can be defined by means of the set of its possible outcomes (sample space) and the ability of observation of the experimenter. It is usually assumed that this ability allows the experimenter to describe the observable events as subsets of the sample space. In this paper, we will consider that the experimenter can only express the...

Special Functions and Pathways for Problems in Astrophysics: An Essay in Honor of A.M. Mathai

Haubold, Hans, Kumar, Dilip, Nair, Seema, Joseph, Dhannya (2010)

Fractional Calculus and Applied Analysis

The paper provides a review of A.M. Mathai's applications of the theory of special functions, particularly generalized hypergeometric functions, to problems in stellar physics and formation of structure in the Universe and to questions related to reaction, diffusion, and reaction-diffusion models. The essay also highlights Mathai's recent work on entropic, distributional, and differential pathways to basic concepts in statistical mechanics, making use of his earlier research results in information...

Spontaneous clustering in theoretical and some empirical stationary processes*

T. Downarowicz, Y. Lacroix, D. Léandri (2010)

ESAIM: Probability and Statistics

In a stationary ergodic process, clustering is defined as the tendency of events to appear in series of increased frequency separated by longer breaks. Such behavior, contradicting the theoretical “unbiased behavior” with exponential distribution of the gaps between appearances, is commonly observed in experimental processes and often difficult to explain. In the last section we relate one such empirical example of clustering, in the area of marine technology. In the theoretical part of the paper...

Stochastic control optimal in the Kullback sense

Jan Šindelář, Igor Vajda, Miroslav Kárný (2008)

Kybernetika

The paper solves the problem of minimization of the Kullback divergence between a partially known and a completely known probability distribution. It considers two probability distributions of a random vector ( u 1 , x 1 , ... , u T , x T ) on a sample space of 2 T dimensions. One of the distributions is known, the other is known only partially. Namely, only the conditional probability distributions of x τ given u 1 , x 1 , ... , u τ - 1 , x τ - 1 , u τ are known for τ = 1 , ... , T . Our objective is to determine the remaining conditional probability distributions of u τ given u 1 , x 1 , ... , u τ - 1 , x τ - 1 such...

Stochastic domination for iterated convolutions and catalytic majorization

Guillaume Aubrun, Ion Nechita (2009)

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

We study how iterated convolutions of probability measures compare under stochastic domination. We give necessary and sufficient conditions for the existence of an integer n such that μ*n is stochastically dominated by ν*n for two given probability measures μ and ν. As a consequence we obtain a similar theorem on the majorization order for vectors in Rd. In particular we prove results about catalysis in quantum information theory.

Su una generalizzazione della nozione di diramatività in teoria dell'informazione.

C. Bertoluzza, I. Bonzani (1983)

Stochastica

The notion of g-locality was introduced in order to generalize the branching one. This notion seems to represent the characteristic property of the entropies which can be utilized in the inquiring processes.In this paper we have characterized all the g-local entropies by determining the whole class of the locality laws.

Sur les mesures du degré de flou.

Enric Trillas, Claudi Alsina (1979)

Stochastica

On caractérise toutes les entropies-floues qui sont des valuations des treillis P(X) des parties floues d'un ensemble fini X, on presente la construction de certaines entropies floues et on analyse leur caractère de valuation de treillis aiguisés Sh(g), g belonging to P(X).

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