Smoothing spline ANOVA models / Chong Gu.
By: Gu, Chong
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Material type: 
TextSeries: Springer series in statistics: Publisher: New York : Springer, c2002Description: xiii, 289 p. : ill. ; 25 cm.ISBN: 0387953531 (alk. paper).Subject(s): Analysis of variance | Spline theory | Smoothing (Statistics)DDC classification: 311 LOC classification: QA279.G8 2002| Item type | Current location | Call number | URL | Copy number | Status | Date due | Barcode |
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წიგნი
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ეროვნული სამეცნიერო ბიბლიოთეკა 1 ახალი გამოცემები. დარბ. 4 | Cu31 311 (Browse shelf) | 2E 58650 | 2E58650 | Available | 2010-0323 |
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.
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