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Dealing with Spatiotemporal Heterogeneity: The Generalized BME Model

In: Progress in Spatial Analysis

Author

Listed:
  • Hwa-Lung Yu

    (National Taiwan University)

  • George Christakos
  • Patrick Bogaert

Abstract

Geographical studies involving natural systems and their attributes (e.g., environmental processes, land use parameters, human exposure indicators, disease variables, and financial indexes) often need to quantitatively assess spatiotemporal dependence and generate informative maps of the attributes across space-time. These are important, indeed, goals of spatiotemporal systems modelling and data analysis introduced in a modern statistical framework by Christakos (1990, 1991a,b, 1992). Subsequent works include Goodall and Mardia (1994), Haas (1995), Bogaert (1996), Christakos and Hristopulos (1998), and Kyriakidis and Journel (1999). Among the more recent developments one should notice the works of Serre et al. (2003), Kolovos et al. (2002, 2004), Douaik et al. (2004), Christakos et al. (2002, 2005), Stein (2005), Law et al. (2006), Porcu et al. (2006, 2008), Yu et al. (2007a–c), Renshaw et al. (2008), and Ruiz-Medina et al. (2008a,b).

Suggested Citation

  • Hwa-Lung Yu & George Christakos & Patrick Bogaert, 2010. "Dealing with Spatiotemporal Heterogeneity: The Generalized BME Model," Advances in Spatial Science, in: Antonio Páez & Julie Gallo & Ron N. Buliung & Sandy Dall'erba (ed.), Progress in Spatial Analysis, pages 75-91, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-03326-1_5
    DOI: 10.1007/978-3-642-03326-1_5
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    Cited by:

    1. Daniel Arribas-Bel & Julia Koschinsky & Pedro Amaral, 2012. "Improving the multi-dimensional comparison of simulation results: a spatial visualization approach," Letters in Spatial and Resource Sciences, Springer, vol. 5(2), pages 55-63, July.
    2. repec:asg:wpaper:1046 is not listed on IDEAS

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