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Spatial and Space-Time Processes

In: Long-Memory Processes

Author

Listed:
  • Jan Beran

    (University of Konstanz, Dept. of Mathematics and Statistics)

  • Yuanhua Feng

    (University of Paderborn, Faculty of Business Administration and Economics)

  • Sucharita Ghosh

    (Swiss Federal Research Institute WSL)

  • Rafal Kulik

    (University of Ottawa, Dept. of Mathematics and Statistics)

Abstract

Spatial data play an important role in many areas such as ecology, biology, environmental monitoring, agronomy, remote sensing, geology, to name a few. Sometimes observations are obtained on a regular lattice (see, e.g. Whittle in Biometrika 49:305–314, 1962; Bartlett in Adv. Appl. Prob. 6(2):336–358, 1974; Besag in J. R. Stat. Soc., Ser. B 36(2):192–236, 1974; Cressie in Statistics for spatial data, 1993; Christakos in Random field models in Earth sciences, 1992; Modern spatiotemporal geostatistics, 2000; Benson et al. in Water Resour. Res. 42(W01415):1–18, 2006; Sain and Cressie in J. Econom. 140(1):226–259, 2007, and references therein). This leads to considering spatial processes on a grid, or more specifically, random fields X t with index $t\in\mathbb{Z}^{2}$ . On the other hand, if the spatial points are not on a regular grid, then random fields with $t\in\mathbb{R}^{2}$ are used.

Suggested Citation

  • Jan Beran & Yuanhua Feng & Sucharita Ghosh & Rafal Kulik, 2013. "Spatial and Space-Time Processes," Springer Books, in: Long-Memory Processes, edition 127, chapter 0, pages 753-769, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-35512-7_9
    DOI: 10.1007/978-3-642-35512-7_9
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