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Spatial Process Simulation

Part of the Lecture Notes in Mathematics book series (LNM,volume 2120)

Abstract

The simulation of random spatial data on a computer is an important tool for understanding the behavior of spatial processes. In this chapter we describe how to simulate realizations from the main types of spatial processes, including Gaussian and Markov random fields, point processes, spatial Wiener processes, and Lévy fields. Concrete MATLAB code is provided.

Keywords

  • Poisson Process
  • Intensity Function
  • Fractional Brownian Motion
  • Spatial Process
  • Compound Poisson Process

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Correspondence to Dirk P. Kroese .

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© 2015 Springer International Publishing Switzerland

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Kroese, D.P., Botev, Z.I. (2015). Spatial Process Simulation. In: Schmidt, V. (eds) Stochastic Geometry, Spatial Statistics and Random Fields. Lecture Notes in Mathematics, vol 2120. Springer, Cham. https://doi.org/10.1007/978-3-319-10064-7_12

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