Quelques applications de la théorie générale des processus. I.
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Jacques Azéma (1972)
Inventiones mathematicae
J.B. Walsh, Meyer (1971)
Inventiones mathematicae
A. Brunel, D. Revuz (1974)
Annales de l'I.H.P. Probabilités et statistiques
Paul-André Meyer (1972)
Séminaire de probabilités de Strasbourg
Jacques Azéma, Thierry Jeulin, Frank B. Knight, Marc Yor (1998)
Séminaire de probabilités de Strasbourg
E. Andjel, C. Cocozza-Thivent, M. Roussignol (1985)
Annales de l'I.H.P. Probabilités et statistiques
Marc Yor (1979)
Séminaire de probabilités de Strasbourg
Z. Ciesielski, G. Kerkyacharian, B. Roynette (1993)
Studia Mathematica
The first part of the paper presents results on Gaussian measures supported by general Banach sequence spaces and by particular spaces of Besov-Orlicz type. In the second part, a new constructive isomorphism between the just mentioned sequence spaces and corresponding function spaces is established. Consequently, some results on the support function spaces for the Gaussian measure corresponding to the fractional Brownian motion are proved. Next, an application to stochastic equations is given. The...
M. Petruszewycz (1979)
Mathématiques et Sciences Humaines
D. Lepingle (1976)
Studia Mathematica
Liming Wu (1996)
Annales mathématiques Blaise Pascal
Jacques-Édouard Dies (1982)
Annales de l'I.H.P. Probabilités et statistiques
M. Brancovan (1973)
Annales de l'I.H.P. Probabilités et statistiques
Jean Saint Raymond (1978)
Séminaire de probabilités de Strasbourg
János Engländer (2008)
Annales de l'I.H.P. Probabilités et statistiques
We study a spatial branching model, where the underlying motion is d-dimensional (d≥1) brownian motion and the branching rate is affected by a random collection of reproduction suppressing sets dubbed mild obstacles. The main result of this paper is the quenched law of large numbers for the population for all d≥1. We also show that the branching brownian motion with mild obstacles spreads less quickly than ordinary branching brownian motion by giving an upper estimate on its speed. When the underlying...
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