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Structured additive distributional regression for analysing landings per unit effort in fisheries research
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文摘
Structured additive distributional regression models constitute a powerful tool to analyse determinants of and variability in fishery indices. The gamma distribution and the flexible estimation for both first and second order parameters of the distribution describe the LPUE patterns for the particular case as supported by results of the DIC, the quantile residual plots and MSEP. Results also show significant improvements when accounting for the second order parameter. The shape was related to many of the explanatory variables. Mixed models are particularly suitable for unobserved fishing units and for correlated observations in time series analysis, even if our observations represent the whole population of the studied fleet. Fixed effects models are incapable to include variables that are constant for a unit (vessel in this case) and so restrictive for understanding the unobserved heterogeneity.

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