This seminar is part of our Centre’s EC Bayes Seminar Series
Speaker: Mary Llewellyn, University of Edinburgh
Abstract: Inference on the process parameters of a state-space model (SSM) can be especially challenging when the likelihood of the data given the parameters is not available in closed form. A variety of approaches to Bayesian model fitting have been applied in such situations, including MCMC with data augmentation, sequential Monte Carlo (SMC) approximation, and particle MCMC algorithms.
Details:
| Start Date: | 26/05/2022 [add to calendar] |