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On the tails of the distribution of the maximum of a smooth stationary gaussian process

Jean-Marc Azaïs, Jean-Marc Bardet, Mario Wschebor (2002)

ESAIM: Probability and Statistics

We study the tails of the distribution of the maximum of a stationary gaussian process on a bounded interval of the real line. Under regularity conditions including the existence of the spectral moment of order 8, we give an additional term for this asymptotics. This widens the application of an expansion given originally by Piterbarg [11] for a sufficiently small interval.

On the tails of the distribution of the maximum of a smooth stationary Gaussian process

Jean-Marc Azaïs, Jean-Marc Bardet, Mario Wschebor (2010)

ESAIM: Probability and Statistics

We study the tails of the distribution of the maximum of a stationary Gaussian process on a bounded interval of the real line. Under regularity conditions including the existence of the spectral moment of order 8, we give an additional term for this asymptotics. This widens the application of an expansion given originally by Piterbarg [CITE] for a sufficiently small interval.

On uniform tail expansions of multivariate copulas and wide convergence of measures

Piotr Jaworski (2006)

Applicationes Mathematicae

The theory of copulas provides a useful tool for modeling dependence in risk management. In insurance and finance, as well as in other applications, dependence of extreme events is particularly important, hence there is a need for a detailed study of the tail behaviour of multivariate copulas. We investigate the class of copulas having regular tails with a uniform expansion. We present several equivalent characterizations of uniform tail expansions. Next, basing on them, we determine the class of...

On univariate and bivariate aging for dependent lifetimes with Archimedean survival copulas

Franco Pellerey (2008)

Kybernetika

Let 𝐗 = ( X , Y ) be a pair of exchangeable lifetimes whose dependence structure is described by an Archimedean survival copula, and let 𝐗 t = [ ( X - t , Y - t ) | X > t , Y > t ] denotes the corresponding pair of residual lifetimes after time t , with t 0 . This note deals with stochastic comparisons between 𝐗 and 𝐗 t : we provide sufficient conditions for their comparison in usual stochastic and lower orthant orders. Some of the results and examples presented here are quite unexpected, since they show that there is not a direct correspondence between univariate...

On Weak Tail Domination of Random Vectors

Rafał Latała (2009)

Bulletin of the Polish Academy of Sciences. Mathematics

Motivated by a question of Krzysztof Oleszkiewicz we study a notion of weak tail domination of random vectors. We show that if the dominating random variable is sufficiently regular then weak tail domination implies strong tail domination. In particular, a positive answer to Oleszkiewicz's question would follow from the so-called Bernoulli conjecture. We also prove that any unconditional logarithmically concave distribution is strongly dominated by a product symmetric exponential measure.

On Wiener–Hopf factors for stable processes

Piotr Graczyk, Tomasz Jakubowski (2011)

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

We give a series representation of the logarithm of the bivariate Laplace exponent κ of α-stable processes for almost all α ∈ (0, 2].

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