Advances in Bayesian model development and inversion in multivariate inverse inference problems : with application to palaeoclimate reconstruction

Abstract

An extremely challenging example of a multivariate inverse inference problem is the statistical reconstruction of palaeoclimate from fossil pollen data, which represents the motivating research problem considered in this thesis. The model training dataset, consisting of highly multivariate, zero-inflated compositional counts for vegetation, as well as measurements on several climate covariates, presents numerous challenges of model choice and inference. The addressing of these challenges provides the focus for the research contributions presented herein.