Star Wars Sale
 
 

Special Offers see all

Enter to WIN!

Weekly drawing for $100 credit. Subscribe to PowellsBooks.news for a chance to win.
Privacy Policy

More at Powell's


Recently Viewed clear list


Original Essays | June 20, 2014

Lisa Howorth: IMG So Many Books, So Many Writers



I'm not a bookseller, but I'm married to one, and Square Books is a family. And we all know about families and how hard it is to disassociate... Continue »
  1. $18.20 Sale Hardcover add to wish list

    Flying Shoes

    Lisa Howorth 9781620403013

spacer
Qualifying orders ship free.
$242.25
New Hardcover
Ships in 1 to 3 days
Add to Wishlist
available for shipping or prepaid pickup only
Available for In-store Pickup
in 7 to 12 days
Qty Store Section
25 Remote Warehouse Mathematics- Probability and Statistics

This title in other editions

A Distribution-Free Theory of Nonparametric Regression (Springer Series in Statistics)

by

A Distribution-Free Theory of Nonparametric Regression (Springer Series in Statistics) Cover

 

Synopses & Reviews

Publisher Comments:

This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates such as classical local averaging estimates including kernel, partitioning and nearest neighbor estimates, least squares estimates using splines, neural networks and radial basis function networks, penalized least squares estimates, local polynomial kernel estimates, and orthogonal series estimates. The emphasis is on distribution-free properties of the estimates. Most consistency results are valid for all distributions of the data. Whenever it is not possible to derive distribution-free results, as in the case of the rates of convergence, the emphasis is on results which require as few constrains on distributions as possible, on distribution-free inequalities, and on adaptation. The relevant mathematical theory is systematically developed and requires only a basic knowledge of probability theory. The book will be a valuable reference for anyone interested in nonparametric regression and is a rich source of many useful mathematical techniques widely scattered in the literature. In particular, the book introduces the reader to empirical process theory, martingales and approximation properties of neural networks.

Synopsis:

 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.

Synopsis:

This monograph presents a modern approach to nonparametric regression with random design. The relevant mathematical theory is systematically developed and requires only a basic knowledge of probability theory. The book will be a valuable reference for anyone interested in nonparametric regression and is a rich source of many useful mathematical techniques widely scattered in the literature. In particular, the book introduces the reader to empirical process theory, martingales and approximation properties of neural networks.

Table of Contents

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

Product Details

ISBN:
9780387954417
Author:
Gyorfi, Laszlo
Author:
Kohler, Michael
Author:
Krzyzak, Adam
Author:
Gyrfi, Lszl
Author:
Walk, Harro
Publisher:
Springer
Location:
New York, NY
Subject:
Statistics
Subject:
Regression analysis
Subject:
Distribution
Subject:
Nonparametric statistics
Subject:
Distribution (Probability theory)
Subject:
Probability & Statistics - General
Subject:
Statistical Theory and Methods
Subject:
Mathematics | Probability and Statistics
Subject:
Language, literature and biography
Subject:
mathematics and statistics
Subject:
Mathematical statistics
Copyright:
Edition Number:
1
Edition Description:
Book
Series:
Springer Series in Statistics
Series Volume:
no. 68
Publication Date:
20020831
Binding:
HARDCOVER
Language:
English
Illustrations:
Yes
Pages:
664
Dimensions:
235 x 155 mm 2450 gr

Other books you might like

  1. Commensurabilities Among Lattices in... New Trade Paper $82.75
  2. A Probabilistic Theory of Pattern... New Hardcover $135.25
  3. Geometric Group Theory: Proceedings... New Hardcover $120.25
  4. Word Processing in Groups New Hardcover $111.75

Related Subjects

Science and Mathematics » Mathematics » Applied
Science and Mathematics » Mathematics » General
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics
Science and Mathematics » Physics » Fluid Mechanics

A Distribution-Free Theory of Nonparametric Regression (Springer Series in Statistics) New Hardcover
0 stars - 0 reviews
$242.25 In Stock
Product details 664 pages Springer-Verlag - English 9780387954417 Reviews:
"Synopsis" by ,  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.
"Synopsis" by , This monograph presents a modern approach to nonparametric regression with random design. The relevant mathematical theory is systematically developed and requires only a basic knowledge of probability theory. The book will be a valuable reference for anyone interested in nonparametric regression and is a rich source of many useful mathematical techniques widely scattered in the literature. In particular, the book introduces the reader to empirical process theory, martingales and approximation properties of neural networks.
spacer
spacer
  • back to top
Follow us on...




Powell's City of Books is an independent bookstore in Portland, Oregon, that fills a whole city block with more than a million new, used, and out of print books. Shop those shelves — plus literally millions more books, DVDs, and gifts — here at Powells.com.