Parameter estimation in multi particle Lagrangian stochastic models.

A class of multi particle Lagrangian stochastic models is considered mimicking 2 D 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. [ABSTRACT FROM AUTHOR]