Simulation of spatial models
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.
KeywordsMarkov Chain Monte Carlo Markov Chain Spatial Model Gibbs Sampling Monte Carlo Markov Chain Method
Unable to display preview. Download preview PDF.