The methodological research of the group is Bayesian in nature. Areas of research include hierarchical multivariate random effects models, wavelets, nonparametric regression and resampling. There is a strong interest in applications with specific areas being forensic science, the law, agriculture, and functional genomics data such as gene expression microarrays.

Statistics research group

Items in this Collection

  • Fast methods for training Gaussian processes 

    Moore, Christopher J; Chua, Alvin J K; Berry, Christopher P L; Gair, Jonathan R
    This submission includes a simplified version of some code we have been developing for fast training of Gaussian processes. We also include a sample data set, which is NOAA tidal data from Woods Hole in the US, downloaded ...