Semiparametric regression during 2003-2007. Academic Article

abstract

• 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.

authors

• Carroll, Raymond

published proceedings

• Electron J Stat

altmetric score

• 13.35

author list (cited authors)

• Ruppert, D., Wand, M. P., & Carroll, R. J.

citation count

• 185

complete list of authors

• Ruppert, David||Wand, MP||Carroll, Raymond J

publication date

• January 2009

publisher

• Institute of Mathematical Statistics  Publisher

published in

• Electronic Journal of Statistics  Journal

keywords

• Asymptotics
• Boosting
• Bugs
• Functional Data Analysis
• Generalized Linear Mixed Models
• Graphical Models
• Hierarchical Bayesian Models
• Kernel Machines
• Longitudinal Data Analysis
• Mixed Models
• Monte Carlo Methods
• Penalized Splines
• Spatial Statistics

PubMed Central ID

• 20305800

Digital Object Identifier (DOI)

• 10.1214/09-EJS525

URI

• https://hdl.handle.net/1969.1/178779

start page

• 1193

end page

• 1256

volume

• 3

issue

• none