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A comparative study of simulation methods for marked Gibbs processes

Published online by Cambridge University Press:  01 July 2016

Jorge Mateu
Affiliation:
Universitat Jaume I
Francisco Montes
Affiliation:
Universitat de Valencia

Abstract

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Type
Papers
Copyright
Copyright © Applied Probability Trust 1998 

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References

[1] Baddeley, A.J and Møller, J. (1989). Nearest-neighbour Markov point processes and randomsets. Internat. Statist. Review 57, 90121.Google Scholar
[2] Geyer, C. and Moller, j. (1994). Simulation procedures and likelihood inference for spatial point processes. Scand. J. Statist. 21, 359373.Google Scholar
[3] Ripley, B.D. (1977). Modelling spatial patterns (with discussion). J. Roy. Statist. Soc. B 39, 172212.Google Scholar
[4] Ripley, B.D. (1988). Statistical Inference for Spatial Processes. Cambridge University Press, Cambridge, pp. 4973.Google Scholar
[5] Stoyan, D. and Grabarnik, P. (1991). Second-order characteristics for stochastic structures connected with Gibbs point processes. Math. Nachr. 151, 95100.Google Scholar
[6] Stoyan, D., Kendall, W.S. and Mecke, J. (1995). Stochastic Geometry and its Applications, 2nd edn. Wiley, New York, pp. 166192.Google Scholar