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Calibration and evaluation of individual-based models using Approximate Bayesian Computation

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  • van der Vaart, Elske
  • Beaumont, Mark A.
  • Johnston, Alice S.A.
  • Sibly, Richard M.

Abstract

This paper investigates the feasibility of using Approximate Bayesian Computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain.

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  • van der Vaart, Elske & Beaumont, Mark A. & Johnston, Alice S.A. & Sibly, Richard M., 2015. "Calibration and evaluation of individual-based models using Approximate Bayesian Computation," Ecological Modelling, Elsevier, vol. 312(C), pages 182-190.
    • Handle: RePEc:eee:ecomod:v:312:y:2015:i:c:p:182-190
    DOI: 10.1016/j.ecolmodel.2015.05.020
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    Cited by:

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    7. George Karabatsos, 2023. "Approximate Bayesian computation using asymptotically normal point estimates," Computational Statistics, Springer, vol. 38(2), pages 531-568, June.
    8. Clark, Matt & Andrews, Jeffrey & Kolarik, Nicholas & Omar, Mbarouk Mussa & Hillis, Vicken, 2024. "Causal attribution of agricultural expansion in a small island system using approximate Bayesian computation," Land Use Policy, Elsevier, vol. 137(C).
    9. van der Vaart, Elske & Johnston, Alice S.A. & Sibly, Richard M., 2016. "Predicting how many animals will be where: How to build, calibrate and evaluate individual-based models," Ecological Modelling, Elsevier, vol. 326(C), pages 113-123.
    10. Juan Manuel Morales & Agustina Virgilio & María Delgado & Otso Ovaskainen, 2017. "A General Approach to Model Movement in (Highly) Fragmented Patch Networks," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(3), pages 393-412, September.
    11. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.
    12. Evans, Luke C. & Sibly, Richard M. & Thorbek, Pernille & Sims, Ian & Oliver, Tom H. & Walters, Richard J., 2019. "Quantifying the effectiveness of agri-environment schemes for a grassland butterfly using individual-based models," Ecological Modelling, Elsevier, vol. 411(C).
    13. Cartwright, Samantha J. & Bowgen, Katharine M. & Collop, Catherine & Hyder, Kieran & Nabe-Nielsen, Jacob & Stafford, Richard & Stillman, Richard A. & Thorpe, Robert B. & Sibly, Richard M., 2016. "Communicating complex ecological models to non-scientist end users," Ecological Modelling, Elsevier, vol. 338(C), pages 51-59.
    14. Boult, Victoria L. & Quaife, Tristan & Fishlock, Vicki & Moss, Cynthia J. & Lee, Phyllis C. & Sibly, Richard M., 2018. "Individual-based modelling of elephant population dynamics using remote sensing to estimate food availability," Ecological Modelling, Elsevier, vol. 387(C), pages 187-195.
    15. Tuong Manh Vu & Charlotte Probst & Alexandra Nielsen & Hao Bai & Petra S. Meier & Charlotte Buckley & Mark Strong & Alan Brennan & Robin Purhouse, 2020. "A Software Architecture for Mechanism-Based Social Systems Modelling in Agent-Based Simulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(3), pages 1-1.
    16. Zhang, Jingjing & Dennis, Todd E. & Landers, Todd J. & Bell, Elizabeth & Perry, George L.W., 2017. "Linking individual-based and statistical inferential models in movement ecology: A case study with black petrels (Procellaria parkinsoni)," Ecological Modelling, Elsevier, vol. 360(C), pages 425-436.
    17. Troost, Christian & Huber, Robert & Bell, Andrew R. & van Delden, Hedwig & Filatova, Tatiana & Le, Quang Bao & Lippe, Melvin & Niamir, Leila & Polhill, J. Gareth & Sun, Zhanli & Berger, Thomas, 2023. "How to keep it adequate: A protocol for ensuring validity in agent-based simulation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 159, pages 1-21.
    18. de Jager, Monique & Hengeveld, Geerten M. & Mooij, Wolf M. & Slooten, Elisabeth, 2019. "Modelling the spatial dynamics of Maui dolphins using individual-based models," Ecological Modelling, Elsevier, vol. 402(C), pages 59-65.
    19. Walker, Nicola D. & Boyd, Robin & Watson, Joseph & Kotz, Max & Radford, Zachary & Readdy, Lisa & Sibly, Richard & Roy, Shovonlal & Hyder, Kieran, 2020. "A spatially explicit individual-based model to support management of commercial and recreational fisheries for European sea bass Dicentrarchus labrax," Ecological Modelling, Elsevier, vol. 431(C).
    20. Chapron, Guillaume & Wikenros, Camilla & Liberg, Olof & Wabakken, Petter & Flagstad, Øystein & Milleret, Cyril & Månsson, Johan & Svensson, Linn & Zimmermann, Barbara & Åkesson, Mikael & Sand, Håkan, 2016. "Estimating wolf (Canis lupus) population size from number of packs and an individual based model," Ecological Modelling, Elsevier, vol. 339(C), pages 33-44.
    21. Boyd, Robin & Roy, Shovonlal & Sibly, Richard & Thorpe, Robert & Hyder, Kieran, 2018. "A general approach to incorporating spatial and temporal variation in individual-based models of fish populations with application to Atlantic mackerel," Ecological Modelling, Elsevier, vol. 382(C), pages 9-17.

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