Dynamical inference of hidden biological populations.

Luchinsky, Dmitri G. and Smelyanskiy, V. N. and Millonas, M. and McClintock, Peter V. E. (2008) Dynamical inference of hidden biological populations. European Physical Journal B, 65 (3). pp. 369-377. ISSN 1434-6028

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Abstract

Population fluctuations in a predator-prey system are analyzed for the case where the number of prey could be determined, subject to measurement noise, but the number of predators was unknown. The problem of how to infer the unmeasured predator dynamics, as well as the model parameters, is addressed. Two solutions are suggested. In the first of these, measurement noise and the dynamical noise in the equation for predator population are neglected; the problem is reduced to a one-dimensional case, and a Bayesian dynamical inference algorithm is employed to reconstruct the model parameters. In the second solution a full-scale Markov Chain Monte Carlo simulation is used to infer both the unknown predator trajectory, and also the model parameters, using the one-dimensional solution as an initial guess.

Item Type: Journal Article
Journal or Publication Title: European Physical Journal B
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1140/epjb/e2008-00340-5
Uncontrolled Keywords: /dk/atira/pure/researchoutput/libraryofcongress/qc
Subjects:
Departments: Faculty of Science and Technology > Physics
ID Code: 22884
Deposited By: Professor P. V. E. McClintock
Deposited On: 06 Jan 2009 15:18
Refereed?: Yes
Published?: Published
Last Modified: 17 Aug 2019 00:29
URI: https://eprints.lancs.ac.uk/id/eprint/22884

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