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...

書誌詳細
第一著者:	Vollmer, S
フォーマット:	Journal article
言語:	English
出版事項:	2013

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