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Variance Reduction in Smoothing Splines

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Author Info
ROBERT L. PAIGE
SHAN SUN
KEYI WANG
Abstract

We develop a variance reduction method for smoothing splines. For a given point of estimation, we define a variance-reduced spline estimate as a linear combination of classical spline estimates at three nearby points. We first develop a variance reduction method for spline estimators in univariate regression models. We then develop an analogous variance reduction method for spline estimators in clustered/longitudinal models. Simulation studies are performed which demonstrate the efficacy of our variance reduction methods in finite sample settings. Finally, a real data analysis with the motorcycle data set is performed. Here we consider variance estimation and generate 95% pointwise confidence intervals for the unknown regression function. Copyright (c) 2008 Board of the Foundation of the Scandinavian Journal of Statistics.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9469.2008.00616.x
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Publisher Info
Article provided by Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association and Swedish Statistical Association in its journal Scandinavian Journal of Statistics.

Volume (Year): 36 (2009)
Issue (Month): 1 ()
Pages: 112-126
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Handle: RePEc:bla:scjsta:v:36:y:2009:i:1:p:112-126

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This page was last updated on 2009-12-19.


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