Marginal longitudinal semiparametric regression via penalized splines

Title: Marginal longitudinal semiparametric regression via penalized splines
Creator: Ali-Alkadiri, Mohammad; Carroll, R.J.; Wand, M.P.
Date: 2011
Type: Text; Journal article
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/57713
Identifier: vital:4335
Identifier: https://doi.org/doi:10.1016/j.spl.2010.04.002
Identifier: ISSN:0167-7152
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.
Relation: Statistics and Probablitity Letters Vol. 80, no. 15-16 (2011), p. 1242-1252
Rights: Copyright Elsevier
Rights: This metadata is freely available under a CCO license
Subject: 0102 Applied Mathematics; 0104 Statistics; 1403 Econometrics; Additive models; Best prediction; Maximum likelihood; Gibbs sampling; Nonparametric regression; Restricted maximum likelihood; Varying coefficient models
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