Alternative spatiotemporal imputation methods for catch rate standardisation

    Research output: ThesisMaster's Thesis

    115 Downloads (Pure)


    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.
    Original languageEnglish
    Awarding Institution
    • The University of Western Australia
    Award date19 May 2017
    Publication statusUnpublished - 2017


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