Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics.
AU - Smelyanskiy, V. N.
AU - Luchinsky, D. G.
AU - Millonas, M. M.
AU - McClintock, P. V. E.
N1 - This is an open-access item
PY - 2009/5
Y1 - 2009/5
N2 - 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.
AB - 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.
U2 - 10.1088/1367-2630/11/5/053012
DO - 10.1088/1367-2630/11/5/053012
M3 - Journal article
VL - 11, 05
JO - New Journal of Physics
JF - New Journal of Physics
SN - 1367-2630
ER -