Intersecting random translates of invariant Cantor sets.
Intersection Local Times and Tanaka Formulas
Intersection probabilities for a chordal SLE path and a semicircle.
Intersections of randomly embedded sparse graphs are Poisson.
Intertwining of birth-and-death processes
It has been known for a long time that for birth-and-death processes started in zero the first passage time of a given level is distributed as a sum of independent exponentially distributed random variables, the parameters of which are the negatives of the eigenvalues of the stopped process. Recently, Diaconis and Miclo have given a probabilistic proof of this fact by constructing a coupling between a general birth-and-death process and a process whose birth rates are the negatives of the eigenvalues,...
Intertwining of the Wright-Fisher diffusion
It is known that the time until a birth and death process reaches a certain level is distributed as a sum of independent exponential random variables. Diaconis, Miclo and Swart gave a probabilistic proof of this fact by coupling the birth and death process with a pure birth process such that the two processes reach the given level at the same time. Their coupling is of a special type called intertwining of Markov processes. We apply this technique to couple the Wright-Fisher diffusion with reflection...
Interval estimation for the Poisson distribution parameter with a single observation.
Interval partitions and pair interactions
Intrinsic coupling on Riemannian manifolds and polyhedra.
Intrinsic location parameter of a diffusion process.
Intrinsic Stochastic Processes.
Intrinsic volumes and f-vectors of random polytopes.
Introducing randomness into first-order and second-order deterministic differential equations.
Introduction à l'étude des mouvements browniens à plusieurs paramètres
Introduction à une formulation stochastique d'une réaction magnétocatalytique
Introduction au calcul stochastique
Introduction to the Theory of the It-type Stochastic Integrals and Stochastic Differential Equations
Invariance of Poisson measures under random transformations
We prove that Poisson measures are invariant under (random) intensity preserving transformations whose finite difference gradient satisfies a cyclic vanishing condition. The proof relies on moment identities of independent interest for adapted and anticipating Poisson stochastic integrals, and is inspired by the method of Üstünel and Zakai (Probab. Theory Related Fields103 (1995) 409–429) on the Wiener space, although the corresponding algebra is more complex than in the Wiener case. The examples...
Invariance of relative inverse function orderings under compositions of distributions
Bartoszewicz and Benduch (2009) applied an idea of Lehmann and Rojo (1992) to a new setting and used the GTTT transform to define invariance properties and distances of some stochastic orders. In this paper Lehmann and Rojo's idea is applied to the class of models which is based on distributions which are compositions of distribution functions on [0,1] with underlying distributions. Some stochastic orders are invariant with respect to these models.
Invariance of spectral type of a stochastic process with respect to transformation of time.