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Limit state analysis on the un-repeated multiple selection bounded confidence model

Jiangbo Zhang, Yiyi Zhao (2023)

Kybernetika

In this paper, we study the opinion evolution over social networks with a bounded confidence rule. Node initial opinions are independently and identically distributed. At each time step, each node reviews the average opinions of several different randomly selected agents and updates its opinion only when the difference between its opinion and the average is below a threshold. First of all, we provide probability bounds of the opinion convergence and the opinion consensus, are both nontrivial events...

Low-discrepancy point sets for non-uniform measures

Christoph Aistleitner, Josef Dick (2014)

Acta Arithmetica

We prove several results concerning the existence of low-discrepancy point sets with respect to an arbitrary non-uniform measure μ on the d-dimensional unit cube. We improve a theorem of Beck, by showing that for any d ≥ 1, N ≥ 1, and any non-negative, normalized Borel measure μ on [ 0 , 1 ] d there exists a point set x 1 , . . . , x N ∈ [ 0 , 1 ] d whose star-discrepancy with respect to μ is of order D N * ( x 1 , . . . , x N ; μ ) ≪ ( ( l o g N ) ( 3 d + 1 ) / 2 ) / N . For the proof we use a theorem of Banaszczyk concerning the balancing of vectors, which implies an upper bound for the linear discrepancy...

Normalizing constants for a statistic based on logarithms of disjoint m-spacings

Franciszek Czekała (1996)

Applicationes Mathematicae

The paper is concerned with the asymptotic normality of a certain statistic based on the logarithms of disjoint m-spacings. The exact and asymptotic mean and variance are computed in the case of uniform distribution on the interval [0,1]. This result is generalized to the case when the sample is drawn from a distribution with positive step density on [0,1].

Nuevos modelos de distribuciones de extremos basados en aproximaciones en las ramas.

Enrique Castillo, Eladio Moreno, Jaime Puig-Pey (1983)

Trabajos de Estadística e Investigación Operativa

En este trabajo se presenta una metodología que permite clasificar funciones de distribución absolutamente continuas unidimensionales atendiendo a sus ramas. La idea básica es que, en las ramas la función de distribución difiere en un infinitésimo del valor uno o cero dependiendo de la rama de interés. La principal ventaja de esta clasificación es su aplicación a la teoría de distribuciones de extremos. En esta línea se obtienen nuevas familias de distribuciones de extremos. Entre ellas, las clásicas...

On distributions of order statistics for absolutely continuous copulas with applications to reliability

Piotr Jaworski, Tomasz Rychlik (2008)

Kybernetika

Performance of coherent reliability systems is strongly connected with distributions of order statistics of failure times of components. A crucial assumption here is that the distributions of possibly mutually dependent lifetimes of components are exchangeable and jointly absolutely continuous. Assuming absolute continuity of marginals, we focus on properties of respective copulas and characterize the marginal distribution functions of order statistics that may correspond to absolute continuous...

On entropies for random partitions of the unit segment

Milena Bieniek, Dominik Szynal (2008)

Kybernetika

We prove the complete convergence of Shannon’s, paired, genetic and α-entropy for random partitions of the unit segment. We also derive exact expressions for expectations and variances of the above entropies using special functions.

Currently displaying 81 – 100 of 194