IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v482y2023ics0304380023001230.html
   My bibliography  Save this article

Ecological forecasting models: Accuracy versus decisional quality

Author

Listed:
  • Pierre, Jean-Sébastien

Abstract

We consider here forecasting models in ecology or in agronomy, aiming at decision making based upon exceeding a quantitative threshold. We address specifically how to link the intrinsic quality of the model (its accuracy) with its decisional quality, ie its capacity to avoid false decisions and their associated costs. The accuracy of the model can be evaluated by the ρ of the regression of observed values versus estimated ones or by the determination coefficient R2. We show that the decisional quality depends not only of this accuracy but also of the threshold retained to make the decision as well as on the state of nature. The two kinds of decisional errors consists either in deciding no action while an action is required (false negatives) or to act while it is useless (false positives). We also prove that the costs associated to those decisions depend also both of the accuracy of the model and of the value of the decision threshold.

Suggested Citation

  • Pierre, Jean-Sébastien, 2023. "Ecological forecasting models: Accuracy versus decisional quality," Ecological Modelling, Elsevier, vol. 482(C).
  • Handle: RePEc:eee:ecomod:v:482:y:2023:i:c:s0304380023001230
    DOI: 10.1016/j.ecolmodel.2023.110392
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380023001230
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2023.110392?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Karlis, Dimitris & Ntzoufras, Ioannis, 2005. "Bivariate Poisson and Diagonal Inflated Bivariate Poisson Regression Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i10).
    2. Jack W Scannell & Jim Bosley, 2016. "When Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility Crisis," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-21, February.
    3. Biswas, Atanu & Hwang, Jing-Shiang, 2002. "A new bivariate binomial distribution," Statistics & Probability Letters, Elsevier, vol. 60(2), pages 231-240, November.
    4. Volker Grimm & Alice S. A. Johnston & H.-H. Thulke & V. E. Forbes & P. Thorbek, 2020. "Three questions to ask before using model outputs for decision support," Nature Communications, Nature, vol. 11(1), pages 1-3, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luke S. Benz & Michael J. Lopez, 2023. "Estimating the change in soccer’s home advantage during the Covid-19 pandemic using bivariate Poisson regression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 205-232, March.
    2. Tahir Ekin & Stephen Walker & Paul Damien, 2023. "Augmented simulation methods for discrete stochastic optimization with recourse," Annals of Operations Research, Springer, vol. 320(2), pages 771-793, January.
    3. Vijay Viswanathan & Sebastian Tillmanns & Manfred Krafft & Daniel Asselmann, 2018. "Understanding the quality–quantity conundrum of customer referral programs: effects of contribution margin, extraversion, and opinion leadership," Journal of the Academy of Marketing Science, Springer, vol. 46(6), pages 1108-1132, November.
    4. Enes Işık & Özgür Orhangazi, 2022. "Profitability and drug discovery," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(4), pages 891-904.
    5. Bermúdez i Morata, Lluís, 2009. "A priori ratemaking using bivariate Poisson regression models," Insurance: Mathematics and Economics, Elsevier, vol. 44(1), pages 135-141, February.
    6. Lluis Bermúdez i Morata, 2008. "A priori ratemaking using bivariate poisson regression models," Working Papers XREAP2008-09, Xarxa de Referència en Economia Aplicada (XREAP), revised Jul 2008.
    7. Yu, Jihnhee & Kepner, James L. & Bundy, Brian N., 2007. "Exact power calculations for detecting hypotheses involving two correlated binary outcomes," Statistics & Probability Letters, Elsevier, vol. 77(3), pages 288-294, February.
    8. Rómulo A. Chumacero, 2009. "Altitude or Hot Air?," Journal of Sports Economics, , vol. 10(6), pages 619-638, December.
    9. M Ataharul Islam & Rafiqul I Chowdhury, 2017. "A generalized right truncated bivariate Poisson regression model with applications to health data," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-13, June.
    10. Ardo Hout & Graciela Muniz-Terrera, 2019. "Hidden three-state survival model for bivariate longitudinal count data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 529-545, July.
    11. Hofer, Vera & Leitner, Johannes, 2017. "Relative pricing of binary options in live soccer betting markets," Journal of Economic Dynamics and Control, Elsevier, vol. 76(C), pages 66-85.
    12. Bermúdez, Lluís & Karlis, Dimitris, 2011. "Bayesian multivariate Poisson models for insurance ratemaking," Insurance: Mathematics and Economics, Elsevier, vol. 48(2), pages 226-236, March.
    13. Gerling, Charlotte & Drechsler, Martin & Keuler, Klaus & Leins, Johannes A. & Radtke, Kai & Schulz, Björn & Sturm, Astrid & Wätzold, Frank, 2021. "Modelling the cost-effective spatio-temporal allocation of conservation measures in agricultural landscapes facing climate change," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242352, Verein für Socialpolitik / German Economic Association.
    14. Uttam Bandyopadhyay & Joydeep Basu & Ganesh Dutta, 2015. "Crossover design in clinical trials for binary response," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(10), pages 2100-2114, October.
    15. Sobom M. Somé & Célestin C. Kokonendji & Nawel Belaid & Smail Adjabi & Rahma Abid, 2023. "Bayesian local bandwidths in a flexible semiparametric kernel estimation for multivariate count data with diagnostics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 843-865, September.
    16. An, Li & Grimm, Volker & Sullivan, Abigail & Turner II, B.L. & Malleson, Nicolas & Heppenstall, Alison & Vincenot, Christian & Robinson, Derek & Ye, Xinyue & Liu, Jianguo & Lindkvist, Emilie & Tang, W, 2021. "Challenges, tasks, and opportunities in modeling agent-based complex systems," Ecological Modelling, Elsevier, vol. 457(C).
    17. Derek S. Young & Andrew M. Raim & Nancy R. Johnson, 2017. "Zero-inflated modelling for characterizing coverage errors of extracts from the US Census Bureau's Master Address File," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 73-97, January.
    18. Jing-Shiang Hwang & Atanu Biswas, 2008. "Odds ratio for a single 2 × 2 table with correlated binomials for two margins," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(4), pages 483-497, October.
    19. F. Novoa-Muñoz & M. Jiménez-Gamero, 2014. "Testing for the bivariate Poisson distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(6), pages 771-793, August.
    20. J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:482:y:2023:i:c:s0304380023001230. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.