PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Gaussian process functional regression modelling for batch data
J. Q. Shi, B. Wang, Roderick Murray-Smith and Mike Titterington
Biometrics 2006.

Abstract

A Gaussian process functional regression model is proposed for the analysis of batch data. Covariance structure and mean structure are considered simultaneously, with the covariance structure modelled by a Gaussian process regression model and the mean structure modelled by a functional regression model. The model allows the inclusion of covariates in both the covariance structure and the mean structure. It models the nonlinear relationship between a functional output variable and a set of functional and non-functional covariates. Several applications and simulation studies are reported and show that the method provides very good results for curve fitting and prediction.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:2464
Deposited By:Roderick Murray-Smith
Deposited On:22 November 2006