Parameter estimation in multi particle Lagrangian stochastic models

Piterbarg Leonid I.
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Piterbarg Leonid I.: Department of Mathematics, University of Southern California, Kaprielian Hall, Room 108, 3620 Vermont Avenue, Los Angeles, CA 90089-2532

Monte Carlo Methods and Applications, 2006, vol. 12, issue 5, 477-493

Abstract: A class of multi particle Lagrangian stochastic models is considered mimicking 2D turbulence. The maximum likelihood approach is used to estimate their parameters. An error analysis is carried out by Monte Carlo means. The method allows to estimate some physically important characteristics of Lagrangian motion such as relative dispersion and Lyapunov exponent by observing only one particle pair. An illustrative example is given based on real data.

Date: 2006
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DOI: 10.1515/156939606779329044

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