The fortnightly BRAG meeting will be held this Thursday the 27th of June at 1 pm via Zoom/GP-Y801. This week we will have a presentation by Nushrath Najimuddin along with a discussion.
Zoom link:
https://qut.zoom.us/j/89182017555?pwd=C0vJhS5WFNaGkob9bCiX2Kj0MZIxTf.1
Meeting ID: 891 8201 7555
Passcode: 919719
Nushrath’s Talk
Abstract
Bayesian design can be used for efficient data collection over time when the process can be described by a solution to an ordinary differential equation (ODE). Typically, Bayesian designs in such settings are obtained by maximising the expected value of a utility function that is derived from the joint probability distribution of the parameters and the response, given prior information about an appropriate ODE and the ensuing parameter values. However, in practice, appropriately defining such information a priori can be difficult due to incomplete knowledge about the mechanisms that govern how the process evolves over time. In this paper, we propose a method for finding Bayesian designs based on a flexible class of ODEs. Specifically, we consider the inclusion of spline terms into ODEs to provide flexibility in modelling how the process changes over time. We then propose to leverage this flexibility to form designs that are efficient even when the prior information is misspecified. Our approach is motivated by a sampling problem in agriculture where the goal is to provide a better understanding of fruit growth where prior information is based on studies conducted overseas, and therefore is potentially misspecified.