Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/20695
Title: Gaussian process functional regression modeling for batch data.
Authors: Shi, JQ
Wang, B
Murray-Smith, R
Titterington, DM
First Published: Sep-2007
Citation: BIOMETRICS, 2007, 63 (3), pp. 714-723
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.
DOI Link: 10.1111/j.1541-0420.2007.00758.x
ISSN: 0006-341X
Links: http://hdl.handle.net/2381/20695
Type: Journal Article
Appears in Collections:Published Articles, Dept. of Mathematics

Files in This Item:
There are no files associated with this item.


Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.