Journal
ELECTRONIC JOURNAL OF STATISTICS
Volume 3, Issue -, Pages 1193-1256Publisher
INST MATHEMATICAL STATISTICS
DOI: 10.1214/09-EJS525
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
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Funding
- National Cancer Institute [CA57030, CA104620]
- National Science Foundation [DMS-0805975]
- Australian Research Council [DP0877055]
- King Abdullah University of Science and Technology [KUS-CI-016-04]
- NATIONAL CANCER INSTITUTE [R37CA057030] Funding Source: NIH RePORTER
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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.
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