Nonparametric Methods for Curve
Fitting and Prediction with Large Data-sets
EPSRC
GR/T29253/01 (Jan. 2005—June 2007)
Outline
The overall aim of this project is to develop
statistical methodology and the statistical
theory for curve fitting and related problems, focusing particular on the
problems with large data-sets and with large dimensional of input covariates,
and to apply them to the modelling and control of nonlinear dynamic systems in
engineering. We will extend the idea of mixtures and Gaussian processes to
cover a much wider class of models and data structures; to explore ways of
modelling the mean and covariance structures by combining local parametric and
non-parametric approaches; and to develop efficient algorithms suitable for
automatic machine learning and further applications. The core statistical
techniques used in this project to analyse the batch data will enable new
insight into the related engineering problems.
Investigator
Collaborators