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T -law of large numbers for fuzzy numbers

Andrea Marková-Stupňanová (2000)

Kybernetika

The notions of a t -norm and of a fuzzy number are recalled. The law of large numbers for fuzzy numbers is defined. The fuzzy numbers, for which the law of large numbers holds, are investigated. The case when the law of large numbers is violated is studied.

Tail approximations for samples from a finite population with applications to permutation tests

Zhishui Hu, John Robinson, Qiying Wang (2012)

ESAIM: Probability and Statistics

This paper derives an explicit approximation for the tail probability of a sum of sample values taken without replacement from an unrestricted finite population. The approximation is shown to hold under no conditions in a wide range with relative error given in terms of the standardized absolute third moment of the population, β3N. This approximation is used to obtain a result comparable to the well-known Cramér large deviation result in the independent case, but with no restrictions on the sampled...

Tail approximations for samples from a finite population with applications to permutation tests

Zhishui Hu, John Robinson, Qiying Wang (2012)

ESAIM: Probability and Statistics

This paper derives an explicit approximation for the tail probability of a sum of sample values taken without replacement from an unrestricted finite population. The approximation is shown to hold under no conditions in a wide range with relative error given in terms of the standardized absolute third moment of the population, β3N. This approximation is used to obtain a result comparable to the well-known Cramér large deviation result in the independent ...

Tail probability and singularity of Laplace-Stieltjes transform of a Pareto type random variable

Kenji Nakagawa (2015)

Applications of Mathematics

We give a sufficient condition for a non-negative random variable X to be of Pareto type by investigating the Laplace-Stieltjes transform of the cumulative distribution function. We focus on the relation between the singularity at the real point of the axis of convergence and the asymptotic decay of the tail probability. For the proof of our theorems, we apply Graham-Vaaler’s complex Tauberian theorem. As an application of our theorems, we consider the asymptotic decay of the stationary distribution...

Teoría ergódica y simetrización.

Francesc Bofill (1982)

Stochastica

We study the relations between simetrization by a limiting process of probabilities and functions defined on a metric compacy product space and their ergodic properties.

Tessellations of random maps of arbitrary genus

Grégory Miermont (2009)

Annales scientifiques de l'École Normale Supérieure

We investigate Voronoi-like tessellations of bipartite quadrangulations on surfaces of arbitrary genus, by using a natural generalization of a bijection of Marcus and Schaeffer allowing one to encode such structures by labeled maps with a fixed number of faces. We investigate the scaling limits of the latter. Applications include asymptotic enumeration results for quadrangulations, and typical metric properties of randomly sampled quadrangulations. In particular, we show that scaling limits of these...

Testing randomness of spatial point patterns with the Ripley statistic

Gabriel Lang, Eric Marcon (2013)

ESAIM: Probability and Statistics

Aggregation patterns are often visually detected in sets of location data. These clusters may be the result of interesting dynamics or the effect of pure randomness. We build an asymptotically Gaussian test for the hypothesis of randomness corresponding to a homogeneous Poisson point process. We first compute the exact first and second moment of the Ripley K-statistic under the homogeneous Poisson point process model. Then we prove the asymptotic normality of a vector of such statistics for different...

The almost sure central limit theorems for certain order statistics of some stationary Gaussian sequences

Marcin Dudziński (2009)

Annales UMCS, Mathematica

Suppose that X1, X2, … is some stationary zero mean Gaussian sequence with unit variance. Let {kn} be a certain nondecreasing sequence of positive integers, [...] denote the kn largest maximum of X1, … Xn. We aim at proving the almost sure central limit theorems for the suitably normalized sequence [...] under certain additional assumptions on {kn} and the covariance function [...]

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