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A Bayesian approach to estimate the biomass of anchovies off the coast of Perú

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  • Zaida C. Quiroz
  • Marcos O. Prates
  • Håvard Rue

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  • Zaida C. Quiroz & Marcos O. Prates & Håvard Rue, 2015. "A Bayesian approach to estimate the biomass of anchovies off the coast of Perú," Biometrics, The International Biometric Society, vol. 71(1), pages 208-217, March.
    • Handle: RePEc:bla:biomet:v:71:y:2015:i:1:p:208-217
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    File URL: http://hdl.handle.net/10.1111/biom.12227
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    References listed on IDEAS

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    1. Brian Neelon & Pulak Ghosh & Patrick F. Loebs, 2013. "A spatial Poisson hurdle model for exploring geographic variation in emergency department visits," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 389-413, February.
    2. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    3. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    4. Finn Lindgren & Håvard Rue & Johan Lindström, 2011. "An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(4), pages 423-498, September.
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    Cited by:

    1. Rufener, Marie-Christine & Kinas, Paul Gerhard & Nóbrega, Marcelo Francisco & Lins Oliveira, Jorge Eduardo, 2017. "Bayesian spatial predictive models for data-poor fisheries," Ecological Modelling, Elsevier, vol. 348(C), pages 125-134.
    2. Katherine A. L. Valeriano & Victor H. Lachos & Marcos O. Prates & Larissa A. Matos, 2021. "Likelihood‐based inference for spatiotemporal data with censored and missing responses," Environmetrics, John Wiley & Sons, Ltd., vol. 32(3), May.
    3. Ali Arab, 2015. "Spatial and Spatio-Temporal Models for Modeling Epidemiological Data with Excess Zeros," IJERPH, MDPI, vol. 12(9), pages 1-13, August.

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