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Title A distribution-free theory of nonparametric regression / La ́szló Györfi ... [and others]
Published New York : Springer, [2002]
©2002

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Location Call no. Vol. Availability
 W'PONDS  519.536 Gyo/Dft  AVAILABLE
Description xvi, 663 pages : illustrations ; 24 cm
Series Springer series in statistics
Springer series in statistics.
Contents 1. Why Is Nonparametric Regression Important? -- 2. How to Construct Nonparametric Regression Estimates? -- 3. Lower Bounds -- 4. Partitioning Estimates -- 5. Kernel Estimates -- 6. k-NN Estimates -- 7. Splitting the Sample -- 8. Cross-Validation -- 9. Uniform Laws of Large Numbers -- 10. Least Squares Estimates I: Consistency -- 11. Least Squares Estimates II: Rate of Convergence -- 12. Least Squares Estimates III: Complexity Regularization -- 13. Consistency of Data-Dependent Partitioning Estimates -- 14. Univariate Least Squares Spline Estimates -- 15. Multivariate Least Squares Spline Estimates -- 16. Neural Networks Estimates -- 17. Radial Basis Function Networks -- 18. Orthogonal Series Estimates -- 19. Advanced Techniques from Empirical Process Theory -- 20. Penalized Least Squares Estimates I: Consistency -- 21. Penalized Least Squares Estimates II: Rate of Convergence -- 22. Dimension Reduction Techniques -- 23. Strong Consistency of Local Averaging Estimates
24. Semirecursive Estimates -- 25. Recursive Estimates -- 26. Censored Observations -- 27. Dependent Observations
Bibliography Includes bibliographical references (pages [612]-638) and indexes
Notes English
Subject Distribution (Probability theory)
Nonparametric statistics.
Regression analysis.
Author Györfi, László.
LC no. 2002021151
ISBN 0387954414 (alk. paper)