5 papers
Computationally Efficient Experimental Design with Generalized Posteriors
Luke Hagar, James M. McGree
The hybrid approach to experimental design aims to control frequentist operating characteristics of Bayesian decision procedures. These operating characteristics are assessed by si…
A subsampling approach for large data sets when the Generalised Linear Model is potentially misspecified
Amalan Mahendran, Helen Thompson, James M. McGree
Subsampling is a computationally efficient and scalable method to draw inference in large data settings based on a subset of the data rather than needing to consider the whole data…
Bayesian design for mathematical models of fruit growth based on misspecified prior information
Nushrath Najimuddin, David J. Warne, Helen Thompson +1
Bayesian design can be used for efficient data collection over time when the process can be described by the solution to an ordinary differential equation (ODE). Typically, Bayesia…
Gibbs optimal design of experiments
Antony M. Overstall, Jacinta Holloway-Brown, James M. McGree
Bayesian optimal design is a well-established approach to planning experiments. A distribution for the responses, i.e. a statistical model, is assumed which is dependent on unknown…
General Bayesian L2 calibration of mathematical models
Antony M. Overstall, James M. McGree
A mathematical model is a function taking certain arguments and returning a theoretical prediction of a feature of a physical system. The arguments to the mathematical model can be…