All of Nonparametric Statistics

Larry Wasserman - Collection Springer texts in statistics

288 pages, parution le 12/12/2005

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Résumé

The goal of this text is to provide the reader with a single book where they can find a brief account of many, modern topics in nonparametric inference. The book is aimed at Master's level or Ph.D. level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods.

This text covers a wide range of topics including: the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book has a mixture of methods and theory.

L'auteur - Larry Wasserman

Larry is Wasserman is professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathema-tiques de Montreal-Statistical Society of Canada Prize in statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics.

Sommaire

Introduction
Estimating the CDF and Statistical Functions
The Bootstrap and the Jackknife
Smoothing: General Concepts
Nonparametric Regression
Density Estimation
Normal Means and Minimax Theory
Nonparametric Inference Using Orthogonal Functions
Wavelets and Other Adaptive Methods
Other Topics

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Larry Wasserman
Collection	Springer texts in statistics
Parution	12/12/2005
Nb. de pages	288
Format	16 x 24
Couverture	Relié
Poids	530g
Intérieur	Noir et Blanc
EAN13	9780387251455
ISBN13	978-0-387-25145-5