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Robust optimal observation of a metapopulation

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  • Pagendam, D.E.
  • Pollett, P.K.

Abstract

We consider a two-parameter continuous-time Markovian model for patch occupancy in metapopulation, and address the question of when to observe the population in order to obtain the most accurate and precise estimator of the parameters. Using the likelihood obtained from a diffusion approximation we derive a robust procedure for determining the optimal observation schedule, which is considerably simpler than would otherwise be possible. We investigate the performance of two optimality criteria, ED-optimality and a particular form of maximin-optimality. Both allow one to incorporate prior belief about the parameter values before any data is collected. Kernel density estimates of the maximum likelihood estimator are compared under the various combinations of optimality criteria and prior distributions. Our methods are illustrated with reference to a model for the spread of crown of thorns starfish (Acanthaster planci) among the 55 islands comprising the Ryukyu group in Japan.

Suggested Citation

  • Pagendam, D.E. & Pollett, P.K., 2010. "Robust optimal observation of a metapopulation," Ecological Modelling, Elsevier, vol. 221(21), pages 2521-2525.
    • Handle: RePEc:eee:ecomod:v:221:y:2010:i:21:p:2521-2525
    DOI: 10.1016/j.ecolmodel.2010.02.018
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    References listed on IDEAS

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    1. Alex R. Cook & Gavin J. Gibson & Christopher A. Gilligan, 2008. "Optimal Observation Times in Experimental Epidemic Processes," Biometrics, The International Biometric Society, vol. 64(3), pages 860-868, September.
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    Cited by:

    1. Christopher C. Drovandi & Anthony N. Pettitt, 2013. "Bayesian Experimental Design for Models with Intractable Likelihoods," Biometrics, The International Biometric Society, vol. 69(4), pages 937-948, December.
    2. Pagendam, D.E. & Ross, J.V., 2013. "Optimal use of GPS transmitter for estimating species migration rate," Ecological Modelling, Elsevier, vol. 249(C), pages 37-41.
    3. Ross, J.V., 2012. "On parameter estimation in population models III: Time-inhomogeneous processes and observation error," Theoretical Population Biology, Elsevier, vol. 82(1), pages 1-17.

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