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Weak convergence to a Markov process: The martingale approach. (English) Zbl 0794.60074

We obtain some sufficient conditions for weak convergence of a sequence of processes \(\{X_ n\}\) to \(X\), when \(X\) arises as a solution to a well posed martingale problem. These conditions are tailored for application to the case when the state space for the processes \(X_ n\), \(X\) is infinite-dimensional. The usefulness of these conditions is illustrated by deriving Donsker’s invariance principle for Hilbert space valued random variables. Also, continuous dependence of Hilbert space valued diffusions on diffusion and drift coefficients is proved.
Reviewer: A.G.Bhatt

MSC:

60J25 Continuous-time Markov processes on general state spaces
60J35 Transition functions, generators and resolvents
60G44 Martingales with continuous parameter
60G05 Foundations of stochastic processes
Full Text: DOI

References:

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