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Gaussian process functional regression modeling for batch data

Lookup NU author(s): Dr Jian Shi, Dr Bo Wang

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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. © 2007, The International Biometric Society.

Publication metadata

Author(s): Shi JQ, Wang B, Murray-Smith R, Titterington DM

Publication type: Article

Publication status: Published

Journal: Biometrics

Year: 2007

Volume: 63

Issue: 3

Pages: 714-723

ISSN (print): 0006-341X

ISSN (electronic): 1541-0420

Publisher: Wiley-Blackwell Publishing Ltd.

URL: http://dx.doi.org/10.1111/j.1541-0420.2007.00758.x

DOI: 10.1111/j.1541-0420.2007.00758.x

PubMed id: 17825005

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