László Györfi,
Michael Kohler,
Adam Krzyzak,
Harro Walk
e.a.
Springer New York
2002e druk, 2002
9780387954417
A Distribution-Free Theory of Nonparametric Regression
Specificaties
Gebonden, 650 blz.
|
Engels
Springer New York |
2002e druk, 2002
ISBN13: 9780387954417
Rubricering
Onderdeel van serie
Springer Series in Statistics
Levertijd ongeveer 9 werkdagen
Gratis verzonden
Samenvatting
This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.
Specificaties
ISBN13:9780387954417
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:650
Uitgever:Springer New York
Druk:2002
Inhoudsopgave
Why is Nonparametric Regression Important? * How to Construct Nonparametric Regression Estimates * Lower Bounds * Partitioning Estimates * Kernel Estimates * k-NN Estimates * Splitting the Sample * Cross Validation * Uniform Laws of Large Numbers * Least Squares Estimates I: Consistency * Least Squares Estimates II: Rate of Convergence * Least Squares Estimates III: Complexity Regularization * Consistency of Data-Dependent Partitioning Estimates * Univariate Least Squares Spline Estimates * Multivariate Least Squares Spline Estimates * Neural Networks Estimates * Radial Basis Function Networks * Orthogonal Series Estimates * Advanced Techniques from Empirical Process Theory * Penalized Least Squares Estimates I: Consistency * Penalized Least Squares Estimates II: Rate of Convergence * Dimension Reduction Techniques * Strong Consistency of Local Averaging Estimates * Semi-Recursive Estimates * Recursive Estimates * Censored Observations * Dependent Observations