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All Of Nonparametric Statistics Paperback 1

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Author 1
Larry Wasserman
Book Description
This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD 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. It 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's dual approach includes a mixture of methodology and theory.
ISBN-10
1441920447
ISBN-13
9.78144E+12
Language
English
Publisher
Springer-Verlag New York Inc.
Publication Date
11/19/2010
Number of Pages
270
About the Author
Aimed at Masters or PhD level students in statistics, computer science, and engineering, this comprehensive text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference, all set out with exceptional clarity. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. With an exhaustive exploration of asymptotic nonparametric inferences, it also covers a huge range of other crucial topic areas including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book s dual approach includes a mixture of methodology and theory.
Edition Number
1
Editorial Review
"...The book is excellent." (Short Book Reviews of the ISI, June 2006) "Now we have All of Nonparametric Statistics ... the writing is excellent and the author is to be congratulated on the clarity achieved. ... the book is excellent." (N.R. Draper, Short Book Reviews, 26:1, 2006) "Overall, I enjoyed reading this book very much. I like Wasserman's intuitive explanations and careful insights into why one path or approach is taken over another. Most of all, I am impressed with the wealth of information on the subject of asymptotic nonparametric inferences." (Stergios B. Fotopoulos for Technometrics, 49:1, February 2007) "The intention of this book is to give a single source with brief accounts of modern topics in nonparametric inference. ... The text is a mixture of theory and applications, and there are lots of examples ... . The text is also illustrated with many informative figures. ... this book covers many topics of modern nonparametric methods, with focus on estimation and on the construction of confidence sets. It should be a useful reference for anyone interested in the theories and methods of this area." (Andreas Karlsson, Statistical Papers, 48, 2006)