Posterior consistency for Bayesian inverse problems through stability and regression results
In the Bayesian approach, the a priori knowledge about the input of a mathematical model is described via a probability measure. The joint distribution of the unknown input and the data is then conditioned, using Bayes' formula, giving rise to the posterior distribution on the unknown input. In...
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| Médium: | Journal article |
| Jazyk: | English |
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2013
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