IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v38y2011i3p501-512.html
   My bibliography  Save this article

Design issues for population growth models

Author

Listed:
  • J. López Fidalgo
  • I. M. Ortiz Rodr�guez
  • Weng Kee Wong

Abstract

We briefly review and discuss design issues for population growth and decline models. We then use a flexible growth and decline model as an illustrative example and apply optimal design theory to find optimal sampling times for estimating model parameters, specific parameters and interesting functions of the model parameters for the model with two real applications. Robustness properties of the optimal designs are investigated when nominal values or the model is mis-specified, and also under a different optimality criterion. To facilitate use of optimal design ideas in practice, we also introduce a website for generating a variety of optimal designs for popular models from different disciplines.

Suggested Citation

  • J. López Fidalgo & I. M. Ortiz Rodr�guez & Weng Kee Wong, 2011. "Design issues for population growth models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(3), pages 501-512, November.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:3:p:501-512
    DOI: 10.1080/02664760903521419
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664760903521419
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664760903521419?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. Wong, Weng Kee, 1994. "Comparing robust properties of A, D, E and G-optimal designs," Computational Statistics & Data Analysis, Elsevier, vol. 18(4), pages 441-448, November.
    2. Arseniy Karkach, 2006. "Trajectories and models of individual growth," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(12), pages 347-400.
    3. Joy King & Weng-Kee Wong, 2000. "Minimax D-Optimal Designs for the Logistic Model," Biometrics, The International Biometric Society, vol. 56(4), pages 1263-1267, December.
    4. Moerbeek, M., 2005. "Robustness properties of A-, D-, and E-optimal designs for polynomial growth models with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 765-778, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Santiago Campos-Barreiro & Jesús López-Fidalgo, 2015. "D-optimal experimental designs for a growth model applied to a Holstein-Friesian dairy farm," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(3), pages 491-505, September.

    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. Víctor Casero-Alonso & Andrey Pepelyshev & Weng K. Wong, 2018. "A web-based tool for designing experimental studies to detect hormesis and estimate the threshold dose," Statistical Papers, Springer, vol. 59(4), pages 1307-1324, December.
    2. Anna Szczepańska, 2013. "Simultaneous choice of time points and the block design in the growth curve model," Statistical Papers, Springer, vol. 54(2), pages 413-425, May.
    3. 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.
    4. Moerbeek, M., 2005. "Robustness properties of A-, D-, and E-optimal designs for polynomial growth models with autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 765-778, April.
    5. Adewale, Adeniyi J. & Xu, Xiaojian, 2010. "Robust designs for generalized linear models with possible overdispersion and misspecified link functions," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 875-890, April.
    6. Carl-Johan Dalgaard & Casper Worm Hansen & Holger Strulik, 2017. "Accounting for Fetal Origins: Health Capital vs. Health Deficits," Discussion Papers 17-11, University of Copenhagen. Department of Economics.
    7. Akihiro Manabe & Takashi Yamakawa & Shuhei Ohnishi & Tatsuro Akamine & Yoji Narimatsu & Hiroshige Tanaka & Tetsuichiro Funamoto & Yuji Ueda & Takeo Yamamoto, 2018. "A novel growth function incorporating the effects of reproductive energy allocation," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-18, June.
    8. Tekle, Fetene B. & Tan, Frans E.S. & Berger, Martijn P.F., 2008. "Maximin D-optimal designs for binary longitudinal responses," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5253-5262, August.
    9. Belmiro P. M. Duarte & Weng Kee Wong, 2015. "Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming-Based Approach," International Statistical Review, International Statistical Institute, vol. 83(2), pages 239-262, August.
    10. Tjørve, Kathleen M.C. & Tjørve, Even, 2017. "A proposed family of Unified models for sigmoidal growth," Ecological Modelling, Elsevier, vol. 359(C), pages 117-127.
    11. Sheng Wu & Weng Kee Wong & Catherine M. Crespi, 2017. "Maximin optimal designs for cluster randomized trials," Biometrics, The International Biometric Society, vol. 73(3), pages 916-926, September.
    12. R. Sedmák & L. Scheer, 2012. "Modelling of tree diameter growth using growth functions parameterised by least squares and Bayesian methods," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 58(6), pages 245-252.
    13. Chang Li & Daniel C. Coster, 2022. "Improved Particle Swarm Optimization Algorithms for Optimal Designs with Various Decision Criteria," Mathematics, MDPI, vol. 10(13), pages 1-16, July.
    14. Maryam Safarkhani & Mirjam Moerbeek, 2016. "D-optimal designs for a continuous predictor in longitudinal trials with discrete-time survival endpoints," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(2), pages 146-171, May.
    15. Carl‐Johan Dalgaard & Casper Worm Hansen & Holger Strulik, 2021. "Fetal origins—A life cycle model of health and aging from conception to death," Health Economics, John Wiley & Sons, Ltd., vol. 30(6), pages 1276-1290, June.
    16. Karvanen, Juha & Kulathinal, Sangita & Gasbarra, Dario, 2009. "Optimal designs to select individuals for genotyping conditional on observed binary or survival outcomes and non-genetic covariates," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1782-1793, March.
    17. I. Ortiz & I. Martínez & C. Rodríguez & Y. Águila, 2009. "Optimal designs for generalized linear models with biased response," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 70(2), pages 225-237, September.
    18. Eugene C. Ukaegbu & Polycarp E. Chigbu, 2017. "Evaluation of Orthogonally Blocked Central Composite Designs with Partial Replications," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(1), pages 112-141, May.
    19. García-Ródenas, Ricardo & García-García, José Carlos & López-Fidalgo, Jesús & Martín-Baos, José Ángel & Wong, Weng Kee, 2020. "A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    20. Xia, Shujuan & Yamakawa, Takashi & Zhang, Chongliang & Ren, Yiping, 2021. "A multispecies size-structured matrix model incorporating seasonal dynamics," Ecological Modelling, Elsevier, vol. 453(C).

    More about this item

    Statistics

    Access and download statistics

    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:taf:japsta:v:38:y:2011:i:3:p:501-512. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.