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Smoothing spline growth curves with covariates
Authors:Kurt S Riedel  Kaya Imre
Institution:Courant Institute of Mathematical Sciences , New York University , New York, NY, 10012251 Mercer St
Abstract:We adapt the interactive spline model of Wahba. to growth curves o with covariates. The smoothing spline formulation permits a nonpara-metric representation of the growth curves. In the limit when the discretization error is small relative to the estimation error, the resulting growth curve estimates often depend only weakly on the number and locations of the knots. The smoothness parameter is determined from the data by minimizing an empirical estimate of the expected error. We show that the risk estimate of Craven and Wahba is a weighted goodness of fit estimate, A modified loss estimate is given, where a2 is replaced by its unbiased estimate.
Keywords:Growth curves  Smoothing splines  Multivariate analysis  Generalized crossvalidation  Adaptive splines  Fusion physics
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