IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v72y2016i4p1255-1265.html
   My bibliography  Save this article

Mixture of time‐dependent growth models with an application to blue swimmer crab length‐frequency data

Author

Listed:
  • Luke R. Lloyd‐Jones
  • Hien D. Nguyen
  • Geoffrey J. McLachlan
  • Wayne Sumpton
  • You‐Gan Wang

Abstract

Understanding how aquatic species grow is fundamental in fisheries because stock assessment often relies on growth dependent statistical models. Length‐frequency‐based methods become important when more applicable data for growth model estimation are either not available or very expensive. In this article, we develop a new framework for growth estimation from length‐frequency data using a generalized von Bertalanffy growth model (VBGM) framework that allows for time‐dependent covariates to be incorporated. A finite mixture of normal distributions is used to model the length‐frequency cohorts of each month with the means constrained to follow a VBGM. The variances of the finite mixture components are constrained to be a function of mean length, reducing the number of parameters and allowing for an estimate of the variance at any length. To optimize the likelihood, we use a minorization–maximization (MM) algorithm with a Nelder–Mead sub‐step. This work was motivated by the decline in catches of the blue swimmer crab (BSC) (Portunus armatus) off the east coast of Queensland, Australia. We test the method with a simulation study and then apply it to the BSC fishery data.

Suggested Citation

  • Luke R. Lloyd‐Jones & Hien D. Nguyen & Geoffrey J. McLachlan & Wayne Sumpton & You‐Gan Wang, 2016. "Mixture of time‐dependent growth models with an application to blue swimmer crab length‐frequency data," Biometrics, The International Biometric Society, vol. 72(4), pages 1255-1265, December.
  • Handle: RePEc:bla:biomet:v:72:y:2016:i:4:p:1255-1265
    DOI: 10.1111/biom.12531
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/biom.12531
    Download Restriction: no

    File URL: https://libkey.io/10.1111/biom.12531?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
    ---><---

    References listed on IDEAS

    as
    1. You-Gan Wang, 1999. "Estimating Equations for Parameters in Stochastic Growth Models from Tag–Recapture Data," Biometrics, The International Biometric Society, vol. 55(3), pages 900-903, September.
    2. Lloyd-Jones, Luke R. & Wang, You-Gan & Nash, Warwick J., 2014. "Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)," Ecological Modelling, Elsevier, vol. 272(C), pages 311-322.
    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. You-Gan Wang, 2004. "Estimation of Growth Parameters from Multiple-Recapture Data," Biometrics, The International Biometric Society, vol. 60(3), pages 670-675, September.
    2. Lloyd-Jones, Luke R. & Wang, You-Gan & Nash, Warwick J., 2014. "Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)," Ecological Modelling, Elsevier, vol. 272(C), pages 311-322.
    3. Cafarelli, Barbara & Calculli, Crescenza & Cocchi, Daniela & Pignotti, Elettra, 2017. "Hierarchical non-linear mixed-effects models for estimating growth parameters of western Mediterranean solitary coral populations," Ecological Modelling, Elsevier, vol. 346(C), pages 1-9.

    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:bla:biomet:v:72:y:2016:i:4:p:1255-1265. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.