Bayesian Regression Trees, Nonparametric Heteroscedastic Regression Modeling and MCMC Sampling Matthew Pratola, Assistant Professor of Statistics, The Ohio State University Nov 24, 15:00 - 16:00 B1 L2 nonparametric statistics Bayesian Statistics In this talk, we introduce a new Bayesian regression tree model that allows for possible heteroscedasticity in the variance model and devise novel MCMC samplers that appear to adequately explore the posterior tree space of this model.
Uncertainty Quantification of Tsunami Models Serge Guillas, Professor of Statistics, University College London (UCL) Sep 8, 15:00 - 16:00 B1 uncertainty quantification Environmental Statistics In this talk, we first show various strategies for the efficient emulation of simulators having uncertain inputs, with applications to tsunami wave modelling. A fast surrogate of the simulator's time series of outputs is provided by the outer product emulator.