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Leonid I. Piterbarg

Parameter estimation in multi particle Lagrangian stochastic models

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.

Monte Carlo Methods and Applications, Walter de Gruyter

Print ISSN: 0929-9629
Volume: 12, 11/2006
Pages: 477 - 493

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