Computational information geometry: geometry of model choice
- Paul Marriott (University of Waterloo, Waterloo, Canada)
Abstract
Joint work with Karim Anaya-Izquierdo and Frank Critchley (Open University) and Paul Vos (East Carolina).
Our project uses computational information geometry to develop diagnostic tools to help understand sensitivity to model choice by building an appropriate perturbation space for a given inference problem. Focused on generalised linear models, the long-term aim is to engage with statistical practice via appropriate R software encapsulating the underlying geometry, whose details the user may ignore.
This talk exploits the universality of the extended multinomial model to examine the interaction between prior considerations (scientific and otherwise), model choice and final inference. A range of examples are used for illustration. There are strong points of contact with the work of Copas and Eguchi.
EPSRC support under grant EP/E017878/1 is gratefully acknowledged.
