Smoothing with Mixed Model Software

Smoothing with Mixed Model Software

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Smoothing methods that use basis functions with penalization can be formulated as fits in a mixed model framework. One of the major benefits is that software for mixed model analysis can be used for smoothing. We illustrate this for several smoothing models such as additive and varying coefficient m...

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Main Authors: Long Ngo, Matthew P. Wand
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2004-01-01
Series:Journal of Statistical Software
Online Access:http://www.jstatsoft.org/index.php/jss/article/view/2320
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spelling doaj-6168399112934e60ab9b055f92b078032020-11-24T22:31:17ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602004-01-019115410.18637/jss.v009.i01924Smoothing with Mixed Model SoftwareLong NgoMatthew P. WandSmoothing methods that use basis functions with penalization can be formulated as fits in a mixed model framework. One of the major benefits is that software for mixed model analysis can be used for smoothing. We illustrate this for several smoothing models such as additive and varying coefficient models for both S-PLUS and SAS software. Code for each of the illustrations is available on the Internet.http://www.jstatsoft.org/index.php/jss/article/view/2320
collection DOAJ
language English
format Article
sources DOAJ
author Long Ngo
Matthew P. Wand
spellingShingle Long Ngo
Matthew P. Wand
Smoothing with Mixed Model Software
Journal of Statistical Software
author_facet Long Ngo
Matthew P. Wand
author_sort Long Ngo
title Smoothing with Mixed Model Software
title_short Smoothing with Mixed Model Software
title_full Smoothing with Mixed Model Software
title_fullStr Smoothing with Mixed Model Software
title_full_unstemmed Smoothing with Mixed Model Software
title_sort smoothing with mixed model software
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2004-01-01
description Smoothing methods that use basis functions with penalization can be formulated as fits in a mixed model framework. One of the major benefits is that software for mixed model analysis can be used for smoothing. We illustrate this for several smoothing models such as additive and varying coefficient models for both S-PLUS and SAS software. Code for each of the illustrations is available on the Internet.
url http://www.jstatsoft.org/index.php/jss/article/view/2320
work_keys_str_mv AT longngo smoothingwithmixedmodelsoftware
AT matthewpwand smoothingwithmixedmodelsoftware
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