Seminars in Statistics
Seminars in Statistics
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Seminars in Statistics Laura Ventura (University of Padua)
Seminars in Statistics Laura Ventura (University of Padua)
Robust Approximate Bayesian Inference The likelihood function is the basis of both frequentist and Bayesian methods. However, the stability of likelihood-based procedures requires strict adherence to the model assumptions: mild deviations from the model can lead to misleading inferential results. A possible Bayesian solution to robustness is to use a of robust pseudo likelihood, such…
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Seminars in Statistics Richard Nickl (University of Cambridge)
Seminars in Statistics Richard Nickl (University of Cambridge)
Nonparametric Bayesian inference for discretely sampled diffusions We consider the nonlinear statistical inverse problem ofmaking inference on the unknown parameters of a diffusion processdescribing the solution of a stochastic differential equation. Theobservation regime is such that the process is sampled at discretetime points that are a fixed distance apart, and we investigate theasymptotic regime when…