Alternative spatiotemporal imputation methods for catch rate standardisation

    Research output: ThesisMaster's Thesis

    Abstract

    An index of fish abundance is often calculated from the estimated marginal means predicted from a generalised linear model fitted to fishery catch rate data with suitable explanatory variables. However, fishing grounds can change, because fleets often shift their activity to target different areas of a fish population over time, which can lead to spatiotemporal gaps in catch rate data. These missing data, if ignored, may result in a biased index. This thesis develops and evaluates several alternative imputation methods for reducing such biases. Evaluations were done by analysing both simulated and real fisheries datasets.
    LanguageEnglish
    QualificationMasters
    Awarding Institution
    • The University of Western Australia
    Award date19 May 2017
    DOIs
    StateUnpublished - 2017

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    standardization
    fishery
    fish
    method
    rate
    index

    Cite this

    @phdthesis{3ac17eaef8f04ac586aaccdf912db882,
    title = "Alternative spatiotemporal imputation methods for catch rate standardisation",
    abstract = "An index of fish abundance is often calculated from the estimated marginal means predicted from a generalised linear model fitted to fishery catch rate data with suitable explanatory variables. However, fishing grounds can change, because fleets often shift their activity to target different areas of a fish population over time, which can lead to spatiotemporal gaps in catch rate data. These missing data, if ignored, may result in a biased index. This thesis develops and evaluates several alternative imputation methods for reducing such biases. Evaluations were done by analysing both simulated and real fisheries datasets.",
    keywords = "Imputation, Fish, Simulation, Catch rates, Fishery stock assessment, Generalised linear model",
    author = "Marriott, {Ross James}",
    note = "Restricted access until 18 January 2018",
    year = "2017",
    doi = "10.4225/23/594767b6abc7f",
    language = "English",
    school = "The University of Western Australia",

    }

    TY - THES

    T1 - Alternative spatiotemporal imputation methods for catch rate standardisation

    AU - Marriott,Ross James

    N1 - Restricted access until 18 January 2018

    PY - 2017

    Y1 - 2017

    N2 - An index of fish abundance is often calculated from the estimated marginal means predicted from a generalised linear model fitted to fishery catch rate data with suitable explanatory variables. However, fishing grounds can change, because fleets often shift their activity to target different areas of a fish population over time, which can lead to spatiotemporal gaps in catch rate data. These missing data, if ignored, may result in a biased index. This thesis develops and evaluates several alternative imputation methods for reducing such biases. Evaluations were done by analysing both simulated and real fisheries datasets.

    AB - An index of fish abundance is often calculated from the estimated marginal means predicted from a generalised linear model fitted to fishery catch rate data with suitable explanatory variables. However, fishing grounds can change, because fleets often shift their activity to target different areas of a fish population over time, which can lead to spatiotemporal gaps in catch rate data. These missing data, if ignored, may result in a biased index. This thesis develops and evaluates several alternative imputation methods for reducing such biases. Evaluations were done by analysing both simulated and real fisheries datasets.

    KW - Imputation

    KW - Fish

    KW - Simulation

    KW - Catch rates

    KW - Fishery stock assessment

    KW - Generalised linear model

    U2 - 10.4225/23/594767b6abc7f

    DO - 10.4225/23/594767b6abc7f

    M3 - Master's Thesis

    ER -