2013/11/05 by Laurent Decreusefond, Decreusefond, Laurent, Ian Flint +3 · 1 citation
Mathematics · #FOS: Mathematics #Point processes and geometric inequalities #Probability (math.PR) #Random Matrices and Applications #Statistics Theory (math.ST) #Stochastic processes and statistical mechanics #math.PR #math.ST #stat.TH
paper · pdf · doi:10.48550/arxiv.1311.1027
arxiv created 2013/11/05 · openalex publication_date 2013/11/05 · arxiv updated 2013/11/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Determinantal point processes (DPP) serve as a practicable modeling for many applications of repulsive point processes. A known approach for simulation was proposed in \citeHough(2006), which generate the desired distribution point wise through rejection sampling. Unfortunately, the size of rejection could be very large. In this paper, we investigate the application of perfect simulation via coupling from the past (CFTP) on DPP. We give a general framework for perfect simulation on DPP model. It is shown that the limiting sequence of the time-to-coalescence of the coupling is bounded by K|Λ|log K|Λ|. An application is given to the stationary models in DPP.