Posterior consistency for Bayesian inverse problems through stability and regression results

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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Autor principal:	Vollmer, S
Format:	Journal article
Idioma:	English
Publicat:	2013

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