Modelling spatial patterns of distribution and abundance of mussel seed using STAR models

• Autores: María P. Pata, María Xosé Rodríguez Álvarez, Vicente Lustres Pérez, Eugenio Fernández Pulpeiro, Carmen María Cadarso Suárez
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 34, Nº. 1, 2010, págs. 67-78
• Idioma: inglés
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• Resumen

  • As mussel farming depends on sources of natural mussel seed, knowledge of factors is required to regulate both the spatial distribution and abundance of this resource. These spatial patterns were modelled using Bayesian STructured Additive Regression (STAR) models for categorical data, based on a mixed-model representation. We used Bayesian penalized splines for modelling the continuous covariate effects and a Markov random ?eld prior for estimating the spatial effects.

• Referencias bibliográficas
  • Austin, M. P. (2002). Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological...
  • Austin, M. P. (2007). Species distribution models and ecological theory: a critical assessment and some possible new approaches. Ecological...
  • Belitz, C., Brezger, A., Kneib, T. and Lang, S. (2009): BayesX Software for Bayesian inference in structured additive regression models. Version...
  • Besag, J., York, J. and Mollié, A. (1991). Bayesian image restoration with two applications in spatial statistics (with discussion). Annals...
  • Boeck, P. and Wilson, M. eds. (2006). Explanatory Item Response Models: A Generalized Linear and Nonlinear Approach. Springer, New York.
  • Eilers, P. H. C. and Marx, B. D. (1996). Flexible smoothing using B-splines and penalties (with comments and rejoinder). Statistical Science,...
  • Fahrmeir, L. and Lang, S. (2001). Bayesian inference for generalized additive models based on Markov random field priors. Applied Statistics,...
  • Fahrmeir, L., Kneib, T. and Lang, S. (2004). Penalized structured additive regression for space-time data: a Bayesian perspective. Statistica...
  • Guisan, A., Edwards, T. C. and Hastie, T. (2002). Generalized linear and generalized additive models in studies of species distributions:...
  • Kammann, E. E. and Wand, M. P. (2003). Geoadditive models. Journal of the Royal Statistical Society C, 52, 1-18.
  • Kneib, T. (2006). Mixed model based inference in structured additive regression. PhD thesis, Dr.Hut-Verlag.
  • Kneib, T. and Fahrmeir, L. (2006). Structured additive regression for categorical space-time data: a mixed model approach. Biometrics, 62,...
  • Kneib, T., Müller, J. and Hothorn, T. (2008). Spatial smoothing techniques for the assessment of habitat suitability. Environmental and...
  • Lang, S. and Brezger, A. (2004). Bayesian P-splines. Journal of Computational and Graphical Statistics, 13, 183-212.
  • McCullagh, P., Nelder, J. A. (1997). Generalized Linear Models, second ed. Chapman and Hall, London.
  • Underwood, A. J., Chapman, M. G. and Connell, S. D. (2000). Observation s in ecology: you can’t make progress on processes without understanding...
  • Wood, S. N. (2006). Generalized additive models: an introduction with R. CRC Press, Boca Raton, FL.