This contribution concerns statistical inference for parametric models used in stochastic geometry and based on quick and simple simulation free procedures as well as more comprehensive methods based on a maximum likelihood or Bayesian approach combined with Markov chain Monte Carlo (MCMC) techniques. Due to space limitations the focus is on spatial point processes.
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