KAUST Grant NumberKUS-CI-016-04
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AbstractSemiparametric 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.
CitationRuppert D, Wand MP, Carroll RJ (2009) Semiparametric regression during 2003–2007. Electronic Journal of Statistics 3: 1193–1256. Available: http://dx.doi.org/10.1214/09-ejs525.
SponsorsSupported by grants from the National Cancer Institute (CA57030) and the National Science Foundation (DMS-0805975). Supported by a grant from the Australian Research Council (DP0877055). Supported by grants from the National Cancer Institute (CA57030, CA104620), and also in part by award number KUS-CI-016-04 made by the King Abdullah University of Science and Technology.
PublisherInstitute of Mathematical Statistics
JournalElectronic Journal of Statistics
CollectionsPublications Acknowledging KAUST Support
Except where otherwise noted, this item's license is described as Creative Commons Attribution License.
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