Saturday, 20 July 2013

Gaussian Markov random fields and Donald Duck

Gaussian Markov random fields (GMRF) are a powerful tool for making a priori distributions for Bayesian inversion. By suitable parameterisation via latent variables, we can describe a big number of features, for example ionospheric structures. In order to demonstrate the flexibility of  GMRFs, below is the Random Duck demonstration done by drawing random samples of a certain GMRF with varying correlation structure.

video

For more details on Gaussian Markov random fields, see for example correlation priors paper (Roininen et al. 2011).

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