Structured additive distributional regression for analysing landings per unit effort in fisheries research
DOI10.1016/j.mbs.2016.11.016zbMath1367.92103OpenAlexW2557243109WikidataQ39133302 ScholiaQ39133302MaRDI QIDQ730303
Valeria Mamouridis, Thomas Kneib, Francesc Maynou, Nadja Klein, Carmen Cadarso-Suárez
Publication date: 27 December 2016
Published in: Mathematical Biosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.mbs.2016.11.016
mixed modelsMarkov chain Monte Carlo simulationgeneralised additive models for locationlandings per unit effortNorth Atlantic Oscillationnorth-western Mediterraneanred shrimp fisheryscale and shape
Population dynamics (general) (92D25) Environmental economics (natural resource models, harvesting, pollution, etc.) (91B76)
Uses Software
Cites Work
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- Scale-dependent priors for variance parameters in structured additive distributional regression
- Bayesian structured additive distributional regression with an application to regional income inequality in Germany
- Generalized additive models
- Penalising model component complexity: a principled, practical approach to constructing priors
- Generalized structured additive regression based on Bayesian P-splines
- Geoadditive Models
- Inference in Generalized Additive Mixed Models by Using Smoothing Splines
- Semiparametric Regression
- Mixed-Effects Models in S and S-PLUS
- Bayesian Measures of Model Complexity and Fit
- Probabilistic Forecasts, Calibration and Sharpness
- Generalized Additive Models for Location, Scale and Shape
- Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
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