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October 1998 Backfitting in smoothing spline ANOVA
Zhen Luo
Ann. Statist. 26(5): 1733-1759 (October 1998). DOI: 10.1214/aos/1024691355

Abstract

A computational scheme for fitting smoothing spline ANOVA models to large data sets with a (near) tensor product design is proposed. Such data sets are common in spatial-temporal analyses. The proposed scheme uses the backfitting algorithm to take advantage of the tensor product design to save both computational memory and time. Several ways to further speed up the backfitting algorithm, such as collapsing component functions and successive over-relaxation, are discussed. An iterative imputation procedure is used to handle the cases of near tensor product designs. An application to a global historical surface air temperature data set, which motivated this work, is used to illustrate the scheme proposed.

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Zhen Luo. "Backfitting in smoothing spline ANOVA." Ann. Statist. 26 (5) 1733 - 1759, October 1998. https://doi.org/10.1214/aos/1024691355

Information

Published: October 1998
First available in Project Euclid: 21 June 2002

zbMATH: 0929.62043
MathSciNet: MR1673276
Digital Object Identifier: 10.1214/aos/1024691355

Subjects:
Primary: 62G07, 65D10, 65F10
Secondary: 62H11, 65U05, 86A32

Rights: Copyright © 1998 Institute of Mathematical Statistics

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Vol.26 • No. 5 • October 1998
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