Strong Markov Local Dirichlet Processes and Stochastic Differential Equations

This paper states the necessary and sufficient conditions on the natural scale and the measure of convergence of the continuous strong Markov local Dirichlet process in order that the process has a representation in the form of a solution of some stochastic differential equation. The results are app...

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Published in:Theory of probability and its applications 1999-01, Vol.43 (2), p.189-202, Article 331
Main Authors: Engelbert, H. J., Wolf, J.
Format: Article
Language:English
Subjects:
Brownian motion
Markov analysis
Random variables
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description This paper states the necessary and sufficient conditions on the natural scale and the measure of convergence of the continuous strong Markov local Dirichlet process in order that the process has a representation in the form of a solution of some stochastic differential equation. The results are applied to the case of the Bessel process of arbitrary dimension.
doi_str_mv 10.1137/S0040585X97976829
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identifier ISSN: 0040-361X
ispartof Theory of probability and its applications, 1999-01, Vol.43 (2), p.189-202, Article 331
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source SIAM Journals Archive; ABI/INFORM Global
subjects Brownian motion
Markov analysis
Random variables
title Strong Markov Local Dirichlet Processes and Stochastic Differential Equations
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