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A note on stochastic domination and conditional thinning

Part of: Stochastic processes

Published online by Cambridge University Press:  01 July 2016

Sandeep R. Shah
Sandeep R. Shah*
Affiliation:
University of Warwick
*
∗ Postal address: Department of Statistics, University of Warwick, Coventry CV4 7AL, UK. Email address: [email protected]
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Abstract

This note investigates the simulation algorithm proposed by van Lieshout and van Zwet (2001). It is seen that this algorithm generally produces biased samples; the nature of this bias is further explored in a technical report by the author.

Keywords

Perfect samplingconditional Boolean modelconditional thinningstrict stochastic domination

MSC classification

Primary: 60G55: Point processes
Secondary: 60G99: None of the above, but in this section
Type
Stochastic Geometry and Statistical Applications
Information
Advances in Applied Probability , Volume 35 , Issue 4 , December 2003 , pp. 937 - 940
Copyright
Copyright © Applied Probability Trust 2003 

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References

[1] Carter, D. S. and Prenter, P. M. (1972). Exponential spaces and counting processes. Z. Wahrscheinlichkeitsth. 21, 1–19.Google Scholar
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[4] Shah, S. R. (2003). Stochastic domination and conditional thinning in spatial point processes. Tech. Rep. 412, Department of Statistics, University of Warwick.Google Scholar
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[6] Van Lieshout, M. N. M. (2000). Markov Point Processes and Their Applications. Imperial College Press, London.CrossRefGoogle Scholar
[7] Van Lieshout, M. N. M. and van Zwet, E. W. (2001). Exact sampling from conditional Boolean models with applications to maximum likelihood inference. Adv. Appl. Prob. 33, 339–353. Correction: 35 (2003), 362.CrossRefGoogle Scholar