Abstract
Monotonicity and convergence properties of the intensity of hard core Gibbs point processes are investigated and compared to the closest packing density. For such processes simulated tempering is shown to be an efficient alternative to commonly used Markov chain Monte Carlo algorithms. Various spatial characteristics of the pure hard core process are studied based on samples obtained with the simulated tempering algorithm.
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Mase, S., Møller, J., Stoyan, D. et al. Packing Densities and Simulated Tempering for Hard Core Gibbs Point Processes. Annals of the Institute of Statistical Mathematics 53, 661–680 (2001). https://doi.org/10.1023/A:1014662415827
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DOI: https://doi.org/10.1023/A:1014662415827