Semiparametric regression during 2003–2007*

Publication Type:
Journal Article
Electronic Journal of Statistics, 2009, 3 pp. 1193 - 1256
Issue Date:
Full metadata record
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application. © 2009, Institute of Mathematical Statistics. All rights reserved.
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