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...

Полное описание

Библиографические подробности
Главный автор:	Vollmer, S
Формат:	Journal article
Язык:	English
Опубликовано:	2013

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