Results 1 to 10 of about 44 (43)

A generalized clark-ocone formula [PDF]

open access: yes, 2000
60H25 (60H07 60H40 60J55 60J65)We extend the Clark-Ocone formula to a suitable class of generalized Brownian functionals.
Oliveira, Maria João   +2 more
core   +1 more source

Solvability of Kolmogorov-Fokker-Planck equations for vector jump processes and occupation time on hypersurfaces [PDF]

open access: yes, 2001
. We study occupation time on hypersurface for Markov n-dimensional jump processes. Solvability and uniqueness of integro-differential Kolmogorov-Fokker-Planck with generalized functions in coefficients are investigated.
N. G. Dokuchaev
core   +1 more source

On the local time density of the reflecting Brownian bridge

open access: yesInternational Journal of Stochastic Analysis, Volume 13, Issue 2, Page 125-136, 2000., 2000
Expressions for the multi‐dimensional densities of Brownian bridge local time are derived by two different methods: A direct method based on Kac′s formula for Brownian functionals and an indirect one based on a limit theorem for strata of random mappings.
Bernhard Gittenberger, Guy Louchard
wiley   +1 more source

Existence of moments of increasing predictable processes associated with one‐ and two‐parameter potentials

open access: yesInternational Journal of Stochastic Analysis, Volume 12, Issue 2, Page 133-150, 1999., 1998
The criterion and sufficient condition for the existence of moments of one‐parameter increasing predictable processes is presented in terms of an associated potential. The estimates of moments of special functional connected with two‐parameter increasing predictable processes are given in the case when the associated potential is bounded.
Yu. Mishura, Ya. Oltsik
wiley   +1 more source

A super-Brownian motion with a locally infinite catalytic mass [PDF]

open access: yes, 1995
A super-Brownian motion X in IR with "hyperbolic" branching rate %2(b) = 1=b 2 , b 2 IR; is constructed, which symbolically could be described by the formal stochastic equation dX t = 1 2 \DeltaX t dt + p 2%2X t dW t ; t ?
Carl Mueller   +3 more
core   +1 more source

Sojourn times for the Brownian motion

open access: yesInternational Journal of Stochastic Analysis, Volume 11, Issue 3, Page 231-246, 1998., 1998
In this paper explicit formulas are given for the distribution function, the density function and the moments of the sojourn time for the reflecting Brownian motion process.
Lajos Takács
wiley   +1 more source

Sojourn times

open access: yesInternational Journal of Stochastic Analysis, Volume 9, Issue 4, Page 415-426, 1996., 1996
Let {ζ(u), u ≥ 0} be a stochastic process with state space A ∪ B where A and B are disjoint sets. Denote by β(t) the total time spent in state B in the interval (0, t). This paper deals with the problem of finding the distribution of β(t) and the asymptotic distribution of β(t) as t → ∞ for various types of stochastic processes.
Lajos Takács
wiley   +1 more source

Brownian local times

open access: yesInternational Journal of Stochastic Analysis, Volume 8, Issue 3, Page 209-232, 1995., 1995
In this paper explicit formulas are given for the distribution functions and the moments of the local times of the Brownian motion, the reflecting Brownian motion, the Brownian meander, the Brownian bridge, the reflecting Brownian bridge and the Brownian excursion.
Lajos Takács
wiley   +1 more source

On the distribution of the number of vertices in layers of random trees

open access: yesInternational Journal of Stochastic Analysis, Volume 4, Issue 3, Page 175-186, 1991., 1991
Denote by Sn the set of all distinct rooted trees with n labeled vertices. A tree is chosen at random in the set Sn, assuming that all the possible nn−1 choices are equally probable. Define τn(m) as the number of vertices in layer m, that is, the number of vertices at a distance m from the root of the tree. The distance of a vertex from the root is the
Lajos Takács
wiley   +1 more source

An extension of the stochastic sewing lemma and applications to fractional stochastic calculus

open access: yesForum of Mathematics, Sigma
We give an extension of Lê’s stochastic sewing lemma. The stochastic sewing lemma proves convergence in $L_m$ of Riemann type sums $\sum _{[s,t] \in \pi } A_{s,t}$ for an adapted two-parameter stochastic process A, under certain conditions ...
Toyomu Matsuda, Nicolas Perkowski
doaj   +1 more source

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