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TitleSรฉminaire de Probabilitรฉs XXXIV [electronic resource] / edited by Jacques Azรฉma, Michel Ledoux, Michel ร{137}mery, Marc Yor
ImprintBerlin, Heidelberg : Springer Berlin Heidelberg, 2000
Connect tohttp://dx.doi.org/10.1007/BFb0103797
Descript VIII, 440 p. online resource

SUMMARY

This volume contains 19 contributions to various subjects in the theory of (commutative and non-commutative) stochastic processes. It also provides a 145-page graduate course on branching and interacting particle systems, with applications to non-linear filtering, by P. del Moral and L. Miclo


CONTENT

Branching and interacting particle systems approximations of feynman-kac formulae with applications to non-linear filtering -- Exponential inequalities for bessel processes -- On sums of iid random variables indexed by N parameters -- Series of iterated quantum stochastic integrals -- p-variation for families of local times on lines -- Large deviations for some poisson random integrals -- Formes de Dirichlet sur un Espace de Wiener-Poisson. Application au grossissement de filtration -- Saturations of gambling houses -- Convergence of a โ{128}{152}gibbs-boltzmannโ{128}{153} random measure for a typed branching diffusion -- Time dependent subordination and markov processes with jumps -- Marked excursions and random trees -- Laws of the iterated logarithm for the Brownian snake -- On the Onsager-Machlup functional for elliptic diffusion processes -- A unified approach to several inequalities for gaussian and diffusion measures -- Trous spectraux pour certains algorithmes de Mรฉtropolis sur ? -- Comportement asymptotique des fonctions harmoniques sur les arbres -- Asymptotic estimates for the first hitting time of fluctuating additive functionals of Brownian motion -- Monotonicity property for a class of semilinear partial differential equations -- Fast sets and points for fractional Brownian motion -- Some invariance properties (of the laws) of Oconeโ{128}{153}s martingales


Mathematics Probabilities Mathematics Probability Theory and Stochastic Processes



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