TY - BOOK AU - Gu,Chong TI - Smoothing spline ANOVA models T2 - Springer series in statistics SN - 0387953531 (alk. paper) AV - QA279.G8 2002 U1 - 311 PY - 2002/// CY - New York PB - Springer KW - Analysis of variance KW - Spline theory KW - Smoothing (Statistics) N1 - Includes bibliographical references (p. [261]-271) and indexes; 1; Introduction --; 1.1; Estimation Problem and Method --; 1.2; Notation --; 1.3; Decomposition of Multivariate Functions --; 1.4; Case Studies --; 1.5; Scope --; 2; Model Construction --; 2.1; Reproducing Kernel Hilbert Spaces --; 2.2; Smoothing Splines on {1, ...,K} --; 2.3; Polynomial Smoothing Splines on [0,1] --; 2.4; Smoothing Splines on Product Domains --; 2.5; Bayes Model --; 2.6; Minimization of Penalized Functional --; 3; Regression with Gaussian-Type Responses --; 3.1; Preliminaries --; 3.2; Smoothing Parameter Selection --; 3.3; Bayesian Confidence Intervals --; 3.4; Computation: Generic Algorithms --; 3.5; Software --; 3.6; Model Checking Tools --; 3.7; Case Studies --; 3.8; Computation: Special Algorithms --; 4; More Splines --; 4.1; Partial Splines --; 4.2; Splines on the Circle --; 4.3; L-Splines --; 4.4; Thin-Plate Splines --; 5; Regression with Exponential Families --; 5.1; Preliminaries --; 5.2; Smoothing Parameter Selection --; 5.3; Approximate Bayesian Confidence Intervals --; 5.4; Software: R Package gss --; 5.5; Case Studies --; 6; Probability Density Estimation --; 6.1; Preliminaries --; 6.2; Poisson Intensity --; 6.3; Smoothing Parameter Selection --; 6.4; Computation --; 6.5; Case Studies --; 6.6; Biased Sampling and Random Truncation --; 6.7; Conditional Densities --; 6.8; Response-Based Sampling --; 7; Hazard Rate Estimation --; 7.1; Preliminaries --; 7.2; Smoothing Parameter Selection --; 7.3; Case Studies --; 7.4; Penalized Partial Likelihood --; 7.5; Models Parametric in Time --; 8; Asymptotic Convergence --; 8.1; Preliminaries --; 8.2; Rates for Density Estimates --; 8.3; Rates for Hazard Estimates --; 8.4; Rates for Regression Estimates ER -