Prior specification for binary Markov mesh models
Journal article, Peer reviewed
Accepted version
Åpne
Permanent lenke
http://hdl.handle.net/11250/2636133Utgivelsesdato
2019Metadata
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- Institutt for matematiske fag [2533]
- Publikasjoner fra CRIStin - NTNU [38558]
Sammendrag
We propose prior distributions for all parts of the specification of a Markov mesh model. In the formulation, we define priors for the sequential neighborhood, for the parametric form of the conditional distributions and for the parameter values. By simulating from the resulting posterior distribution when conditioning on an observed scene, we thereby obtain an automatic model selection procedure for Markov mesh models. To sample from such a posterior distribution, we construct a reversible jump Markov chain Monte Carlo algorithm (RJMCMC). We demonstrate the usefulness of our prior formulation and the limitations of our RJMCMC algorithm in two examples.