Semiparametric regression during 2003–2007
Copyright policy )Semiparametric regression during 2003–2007
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.
- King Abdullah University of Science and Technology Saudi Arabia
- Texas A&M University United States
- University of Wollongong Australia
- Cornell University United States
Hierarchical Bayesian models, mixed models, Generalized linear models (logistic models), hierarchical Bayesian models, boosting, longitudinal data analysis, penalized splines, Bayesian inference, Boosting, spatial statistics, hierarchical bayesian models, 60G08, Asymptotic properties of nonparametric inference, Physical Sciences and Mathematics, 60G05, graphical models, Nonparametric regression and quantile regression, Mixed models, functional data analysis, Penalized splines, Spatial statistics, 2003, Kernel machines, R, 2007, Computational problems in statistics, Generalized linear mixed models, during, kernel machines, Monte Carlo methods, semiparametric, Research exposition (monographs, survey articles) pertaining to statistics, Functional data analysis, 60-02, asymptotics, generalized linear mixed models, regression, BUGS, Graphical models, Longitudinal data analysis, Nonparametric estimation, Asymptotics
Hierarchical Bayesian models, mixed models, Generalized linear models (logistic models), hierarchical Bayesian models, boosting, longitudinal data analysis, penalized splines, Bayesian inference, Boosting, spatial statistics, hierarchical bayesian models, 60G08, Asymptotic properties of nonparametric inference, Physical Sciences and Mathematics, 60G05, graphical models, Nonparametric regression and quantile regression, Mixed models, functional data analysis, Penalized splines, Spatial statistics, 2003, Kernel machines, R, 2007, Computational problems in statistics, Generalized linear mixed models, during, kernel machines, Monte Carlo methods, semiparametric, Research exposition (monographs, survey articles) pertaining to statistics, Functional data analysis, 60-02, asymptotics, generalized linear mixed models, regression, BUGS, Graphical models, Longitudinal data analysis, Nonparametric estimation, Asymptotics
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