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.
Managing Editor: Sabelfeld, Karl K.
Editorial Board Member: Binder, Kurt / Bouleau, Nicolas / Chorin, Alexandre J. / Dimov, Ivan / Dubus, Alain / Egorov, Alexander D. / Ermakov, Sergei M. / Halton, John H. / Heinrich, Stefan / Kalos, Malvin H. / Lepingle, D. / Makarov, Roman / Mascagni, Michael / Mathe, Peter / Niederreiter, Harald / Platen, Eckhard / Sawford, Brian R. / Schmid, Wolfgang Ch. / Schoenmakers, John / Simonov, Nikolai A. / Sobol, Ilya M. / Spanier, Jerry / Talay, Denis
4 Issues per year
Mathematical Citation Quotient 2011: 0.06
Issues
Volume 19 (2013)
Volume 18 (2012)
Volume 17 (2011)
Volume 16 (2010)
Volume 15 (2009)
Volume 14 (2008)
Volume 13 (2008)
Volume 12 (2006)
Volume 11 (2005)
Volume 10 (2004)
Volume 9 (2003)
Volume 8 (2002)
Volume 6 (2000)
Volume 5 (1999)
Volume 4 (1998)
Volume 3 (1997)
Volume 2 (1996)
Most Downloaded Articles
- Simulation of binary random fields with Gaussian numerical models by Prigarin, Sergei M./ Martin, Andreas and Winkler, Gerhard
- A Green's function Monte Carlo algorithm for the Helmholtz equation subject to Neumann and mixed boundary conditions: Validation with an 1D benchmark problem by Chatterjee, Kausik and Anantapadmanabhan, Akshay
- On convergence of semi-statistical and projection-statistical methods for integral equations by Ivanov, Vladimir M. and Korenevski, Maxim L.
- The generalized van der Corput sequence and its application to numerical integration by Fujita, Takahiko/ Ito, Shunji and Ninomiya, Syoiti
- Masthead
Parameter estimation in multi particle Lagrangian stochastic models
Leonid I. Piterbarg
1Department of Mathematics, University of Southern California, Kaprielian Hall, Room 108, 3620 Vermont Avenue, Los Angeles, CA 90089-2532
Citation Information: Monte Carlo Methods and Applications mcma. Volume 12, Issue 5, Pages 477–493, ISSN (Online) 1569-3961, ISSN (Print) 0929-9629, DOI: 10.1515/156939606779329044,
Publication History:
- Published Online:
Comments (0)