Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics.
A Hamiltonian approach is introduced for the reconstruction of trajectories and models of complex stochastic dynamics from noisy measurements. The method converges even when entire trajectory components are unobservable and the parameters are unknown. It is applied to reconstruct nonlinear models of...
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ftulancaster:oai:eprints.lancs.ac.uk:31239 2023-08-27T04:07:44+02:00 Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. Smelyanskiy, V. N. Luchinsky, D. G. Millonas, M. M. McClintock, P. V. E. 2009-05 application/pdf https://eprints.lancs.ac.uk/id/eprint/31239/ https://eprints.lancs.ac.uk/id/eprint/31239/1/NJP2009LostInfo.pdf https://doi.org/10.1088/1367-2630/11/5/053012 en eng https://eprints.lancs.ac.uk/id/eprint/31239/1/NJP2009LostInfo.pdf Smelyanskiy, V. N. and Luchinsky, D. G. and Millonas, M. M. and McClintock, P. V. E. (2009) Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. New Journal of Physics, 11, 05. ISSN 1367-2630 Journal Article PeerReviewed 2009 ftulancaster https://doi.org/10.1088/1367-2630/11/5/053012 2023-08-03T22:19:16Z A Hamiltonian approach is introduced for the reconstruction of trajectories and models of complex stochastic dynamics from noisy measurements. The method converges even when entire trajectory components are unobservable and the parameters are unknown. It is applied to reconstruct nonlinear models of rodent–predator oscillations in Finnish Lapland and high-Arctic tundra. The projected character of noisy incomplete measurements is revealed and shown to result in a degeneracy of the likelihood function within certain null-spaces. The performance of the method is compared with that of the conventional Markov chain Monte Carlo (MCMC) technique. Article in Journal/Newspaper Arctic Tundra Lapland Lancaster University: Lancaster Eprints Arctic New Journal of Physics 11 5 053012 |
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Lancaster University: Lancaster Eprints |
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ftulancaster |
language |
English |
description |
A Hamiltonian approach is introduced for the reconstruction of trajectories and models of complex stochastic dynamics from noisy measurements. The method converges even when entire trajectory components are unobservable and the parameters are unknown. It is applied to reconstruct nonlinear models of rodent–predator oscillations in Finnish Lapland and high-Arctic tundra. The projected character of noisy incomplete measurements is revealed and shown to result in a degeneracy of the likelihood function within certain null-spaces. The performance of the method is compared with that of the conventional Markov chain Monte Carlo (MCMC) technique. |
format |
Article in Journal/Newspaper |
author |
Smelyanskiy, V. N. Luchinsky, D. G. Millonas, M. M. McClintock, P. V. E. |
spellingShingle |
Smelyanskiy, V. N. Luchinsky, D. G. Millonas, M. M. McClintock, P. V. E. Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. |
author_facet |
Smelyanskiy, V. N. Luchinsky, D. G. Millonas, M. M. McClintock, P. V. E. |
author_sort |
Smelyanskiy, V. N. |
title |
Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. |
title_short |
Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. |
title_full |
Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. |
title_fullStr |
Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. |
title_full_unstemmed |
Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. |
title_sort |
recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. |
publishDate |
2009 |
url |
https://eprints.lancs.ac.uk/id/eprint/31239/ https://eprints.lancs.ac.uk/id/eprint/31239/1/NJP2009LostInfo.pdf https://doi.org/10.1088/1367-2630/11/5/053012 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Tundra Lapland |
genre_facet |
Arctic Tundra Lapland |
op_relation |
https://eprints.lancs.ac.uk/id/eprint/31239/1/NJP2009LostInfo.pdf Smelyanskiy, V. N. and Luchinsky, D. G. and Millonas, M. M. and McClintock, P. V. E. (2009) Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics. New Journal of Physics, 11, 05. ISSN 1367-2630 |
op_doi |
https://doi.org/10.1088/1367-2630/11/5/053012 |
container_title |
New Journal of Physics |
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11 |
container_issue |
5 |
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053012 |
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1775348452310384640 |