Spatial smoothing, Nugget effect and infill asymptotics

For spatio-temporal regression models with observations taken regularly in time but irregularly over space, we investigate the effect of spatial smoothing on the reduction of variance in estimating both parametric and nonparametric regression functions. The processes concerned are stationary in time...

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Main Authors: Lu, Zudi, Tjostheim, D., Yao, Q.
Format: Journal Article
Published: Elsevier 2008
Online Access:http://hdl.handle.net/20.500.11937/35135
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author Lu, Zudi
Tjostheim, D.
Yao, Q.
author_facet Lu, Zudi
Tjostheim, D.
Yao, Q.
author_sort Lu, Zudi
building Curtin Institutional Repository
collection Online Access
description For spatio-temporal regression models with observations taken regularly in time but irregularly over space, we investigate the effect of spatial smoothing on the reduction of variance in estimating both parametric and nonparametric regression functions. The processes concerned are stationary in time but may be nonstationary over space. Our study indicates that under the infill asymptotic framework, the existence of the so-called nugget effect in either regressor process or noise process is necessary for spatial smoothing to reduce the estimation variance. In particular the nugget effect in the regressor process may lead to a faster convergence rate in estimating nonparametric regression functions.
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institution Curtin University Malaysia
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publishDate 2008
publisher Elsevier
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spelling curtin-20.500.11937-351352017-09-13T16:08:23Z Spatial smoothing, Nugget effect and infill asymptotics Lu, Zudi Tjostheim, D. Yao, Q. For spatio-temporal regression models with observations taken regularly in time but irregularly over space, we investigate the effect of spatial smoothing on the reduction of variance in estimating both parametric and nonparametric regression functions. The processes concerned are stationary in time but may be nonstationary over space. Our study indicates that under the infill asymptotic framework, the existence of the so-called nugget effect in either regressor process or noise process is necessary for spatial smoothing to reduce the estimation variance. In particular the nugget effect in the regressor process may lead to a faster convergence rate in estimating nonparametric regression functions. 2008 Journal Article http://hdl.handle.net/20.500.11937/35135 10.1016/j.spl.2008.06.002 Elsevier restricted
spellingShingle Lu, Zudi
Tjostheim, D.
Yao, Q.
Spatial smoothing, Nugget effect and infill asymptotics
title Spatial smoothing, Nugget effect and infill asymptotics
title_full Spatial smoothing, Nugget effect and infill asymptotics
title_fullStr Spatial smoothing, Nugget effect and infill asymptotics
title_full_unstemmed Spatial smoothing, Nugget effect and infill asymptotics
title_short Spatial smoothing, Nugget effect and infill asymptotics
title_sort spatial smoothing, nugget effect and infill asymptotics
url http://hdl.handle.net/20.500.11937/35135