2017
DOI: 10.1016/j.mbs.2016.11.016
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Structured additive distributional regression for analysing landings per unit effort in fisheries research

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Cited by 4 publications
(3 citation statements)
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“…The regression model used thin plate regression spline smooth (Wood, 2006) (Carpenter et al, 2017) via the brms interface for R (Bürkner, 2017). Modelling both the expected (mean) and variance of a functional distributional form is increasingly used in ecological and fisheries settings to better understand the temporal population or catch dynamics (Bjorndal et al, 2019;Mamouridis et al, 2017).…”
Section: Exploring Potential Explanatory Predictors Of Npoa Statusmentioning
confidence: 99%
“…The regression model used thin plate regression spline smooth (Wood, 2006) (Carpenter et al, 2017) via the brms interface for R (Bürkner, 2017). Modelling both the expected (mean) and variance of a functional distributional form is increasingly used in ecological and fisheries settings to better understand the temporal population or catch dynamics (Bjorndal et al, 2019;Mamouridis et al, 2017).…”
Section: Exploring Potential Explanatory Predictors Of Npoa Statusmentioning
confidence: 99%
“…In order to identify the social and economic factors impacting catch rates and account for them in CPUE standardization, it is necessary to assimilate the experiential knowledge of harvesters and processors (Steins et al, 2020;Mackinson, 2022;Steins et al, 2022). Novel modeling tools, such as spatiotemporal delta-generalized linear mixed models, structured additive distributional regression, and simulations further enable researchers to identify bias in and derive population trends from fishery dependent data (Mamouridis et al, 2017;Clegg et al, 2022;Ducharme-Barth et al, 2022;Karp et al, 2022).…”
Section: Introductionmentioning
confidence: 99%
“…In order to identify the social and economic factors impacting catch rates and account for them in CPUE standardization, it is necessary to assimilate the experiential knowledge of harvesters and processors . Novel modeling tools, such as spatiotemporal delta-generalized linear mixed models, structured additive distributional regression, and simulations further enable researchers to identify bias in and derive population trends from fishery dependent data (Mamouridis et al, 2017;Ducharme-Barth et al, 2022;Karp et al, 2022).…”
Section: Introductionmentioning
confidence: 99%