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Gaussian Process Functional Regression Modelling for Batch Data

Shi, J.Q., Wang, B., Murray-Smith, R. and Titterington, D.M. (2007) Gaussian Process Functional Regression Modelling for Batch Data. Biometrics (Journal of the International Biometric Society), 63 ( 3). pp. 714-723. ISSN 1541-0420

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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 modeled by a Gaussian process regression model and the mean structure modeled 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 nonfunctional covariates. Several applications and simulation studies are reported and show that the method provides very good results for curve fitting and prediction.

Item Type: Article
Keywords: Batch data • B-spline • Functional data analysis • Gaussian process functional regression model • Gaussian process regression model • Multiple-step-ahead forecasting • Nonparametric curve fitting
Academic Units: The University of York > Mathematics (York)
Depositing User: York RAE Import
Date Deposited: 13 Aug 2009 14:26
Last Modified: 13 Aug 2009 14:26
Published Version: http://dx.doi.org/10.1111/j.1541-0420.2007.00758.x
Status: Published
Publisher: Wiley-Blackwell
Identification Number: 10.1111/j.1541-0420.2007.00758.x
URI: http://eprints.whiterose.ac.uk/id/eprint/5711

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