Statistics Seminars: Bayesian model updating using subset simulation
22 February 2016 14:00 in CM221
On the one hand, the problem of model updating can be tackled using Bayesian methods: the model parameters to be updated are treated as uncertain and the inference is done in terms of their posterior distribution. On the other hand, the engineering structural reliability problem can be solved by advanced Monte Carlo strategies such as Subset Simulation. Recently, a formulation that connects the Bayesian updating problem and the structural reliability problem has been established. This opens up the possibility of efficient model updating using Subset Simulation. The formulation, called BUS (Bayesian Updating with Structural reliability methods), is based on a rejection principle. Its theoretical correctness and efficiency requires the prudent choice of a multiplier, which has remained an open question. Motivated by this problem, this talk presents a study of BUS. The discussion will lead to a revised formulation that allows Subset Simulation to be used for Bayesian updating without having to choose a multiplier in advance.
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