Simulation of spatial models

Part of the Springer Series in Statistics book series (SSS)


Being able to simulate probability distributions and random variables is useful whenever we lack an analytic solution to a problem, be it combinatorial (number of ways to put 32 dominoes on an 8 × 8 grid), a search for maxima (Bayesian image reconstruction, cf. §2.2.2) or calculating integrals.


Markov Chain Monte Carlo Markov Chain Spatial Model Gibbs Sampling Monte Carlo Markov Chain Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Dipartimento di StatisticaUniversità Ca’ Foscari VeneziaVenezialtaly
  2. 2.SAMOS Université Paris IParisFrance

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