This paper is concerned with the general theme of relating the Large Deviation Principle (LDP) for the invariant measures of stochastic processes to the associated sample path LDP. It is shown that if the sample path deviation function possesses certain structure, then the LDP for the invariant measures is implied by the sample path LDP, no other properties of the stochastic processes in question being material. As an application, we obtain an LDP for the stationary distributions of jump diffusions. Methods of large deviation convergence and idempotent probability play an integral part
The paper concerns itself with establishing large deviation principles for a sequence of stochastic ...
AbstractGaussian White Noise, super-Brownian motion and the diffusion-limit Fleming–Viot process are...
AbstractWe present a method for proving the large-deviation principle for processes with paths in th...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
Let X be a topological space and F denote the Borel σ-field in X. A family of probability measures {...
ABSTRACT. We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes i...
Let X be a topological space and F denote the Borel σ-field in X. A family of probability measures {...
AbstractThe large deviation principle is proved for the rescaled and normalized paths of a Lévy proc...
We discuss the large deviation principle of stochastic processes as random elements of l∞(T). We sho...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
The paper concerns itself with establishing large deviation principles for a sequence of stochastic ...
AbstractGaussian White Noise, super-Brownian motion and the diffusion-limit Fleming–Viot process are...
AbstractWe present a method for proving the large-deviation principle for processes with paths in th...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
Let X be a topological space and F denote the Borel σ-field in X. A family of probability measures {...
ABSTRACT. We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes i...
Let X be a topological space and F denote the Borel σ-field in X. A family of probability measures {...
AbstractThe large deviation principle is proved for the rescaled and normalized paths of a Lévy proc...
We discuss the large deviation principle of stochastic processes as random elements of l∞(T). We sho...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the smal...
The paper concerns itself with establishing large deviation principles for a sequence of stochastic ...
AbstractGaussian White Noise, super-Brownian motion and the diffusion-limit Fleming–Viot process are...
AbstractWe present a method for proving the large-deviation principle for processes with paths in th...