Discretisation-invariant and computationally efficient correlation priors for Bayesian inversion
Abstract We are interested in studying Gaussian Markov random fields as correlation priors for Bayesian inversion. We construct the correlation priors to be discretisation-invariant, which means, loosely speaking, that the discrete priors converge to continuous priors at the discretisation limit. W...
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| Format: | Doctoral Thesis |
| Language: | English |
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University of Oulu
2015
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| Online Access: | http://urn.fi/urn:isbn:9789526207544 http://nbn-resolving.de/urn:isbn:9789526207544 |