Approximately optimal experimental design for heteroscedastic Gaussian process models

This paper presents a greedy Bayesian experimental design criterion for heteroscedastic Gaussian process models. The criterion is based on the Fisher information and is optimal in the sense of minimizing parameter uncertainty for likelihood based estimators. We demonstrate the validity of the criterion under different noise regimes and present experimental results from a rabies simulator to demonstrate the effectiveness of the resulting approximately optimal designs.

Making policy in theory and practice:by Hugh Bochel and Sue Duncan (eds)

Book review: Hugh Bochel and Sue Duncan (eds), Policy Press, 2007, 251 pp. (including references and index), £23 (pb), ISBN: 1861349033

The career of councillors:gender, party and politics. By Catherine Bochel and Hugh M. Bochel, 2000. Pp.143. £37.50 hb.

Book review