Marginal longitudinal semiparametric regression via penalized splines

M. Al Kadiri; R.J. Carroll; M.P. Wand

doi:10.1016/j.spl.2010.04.002

Marginal longitudinal semiparametric regression via penalized splines

M. Al Kadiri, R.J. Carroll, M.P. Wand

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

Original language	English (US)
Pages (from-to)	1242-1252
Number of pages	11
Journal	Statistics & Probability Letters
Volume	80
Issue number	15-16
DOIs	https://doi.org/10.1016/j.spl.2010.04.002
State	Published - Aug 2010
Externally published	Yes

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10.1016/j.spl.2010.04.002

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title = "Marginal longitudinal semiparametric regression via penalized splines",

abstract = "We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.",

author = "{Al Kadiri}, M. and R.J. Carroll and M.P. Wand",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): KUS-CI-016-04 Acknowledgements: Wand{\textquoteright}s research was partially supported by Australian Research Council Discovery Project DP0877055. Carroll{\textquoteright}s research was supported by a grant from the US National Cancer Institute (CA57030) and by Award Number KUS-CI-016-04, made by King Abdullah University of Science and Technology, Saudi Arabia. This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

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doi = "10.1016/j.spl.2010.04.002",

language = "English (US)",

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AU - Carroll, R.J.

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N2 - We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

AB - We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

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Marginal longitudinal semiparametric regression via penalized splines

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