Science and Technology Studies Commons^™

Bayesian Learning And Predictability In A Stochastic Nonlinear Dynamical Model, John Parslow, Noel Cressie, Edward P. Campbell, Emlyn Jones, Lawrence Murray

Professor Noel Cressie

Bayesian inference methods are applied within a Bayesian hierarchical modelling framework to the problems of joint state and parameter estimation, and of state forecasting. We explore and demonstrate the ideas in the context of a simple nonlinear marine biogeochemical model. A novel approach is proposed to the formulation of the stochastic process model, in which ecophysiological properties of plankton communities are represented by autoregressive stochastic processes. This approach captures the effects of changes in plankton communities over time, and it allows the incorporation of literature metadata on individual species into prior distributions for process model parameters. The approach is applied …