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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© 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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DOI: https://doi.org/10.1007/978-3-319-10064-7_12
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10063-0
Online ISBN: 978-3-319-10064-7
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