All of Nonparametric Statistics (Springer Texts in Statistics)

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9781441920447: All of Nonparametric Statistics (Springer Texts in Statistics)

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. The book's dual approach includes a mixture of methodology and theory.

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From the Back Cover:

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.

Larry Wasserman is Professor of Statistics at Carnegie Mellon University and a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, multiple testing, 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 mathématiques 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. He is the author of All of Statistics: A Concise Course in Statistical Inference (Springer, 2003).

Review:

From the reviews:

"...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)

"...ANPS provides an excellent complement or a complete course textbook with a mixture of theoretical and computational exercises. ...For a book in a rapidly evolving field, the content and references are quit eup to date. ...As advertised, it offers a well-written, albeit brief account of numerous topics in modern nonparametric inference." (Greg Ridgeway, Journal of the American Statistical Association, Vol. 102, No. 477, 2007)

"This is a nicely written textbook oriented mainly to master level statistics and computer science students. The author provides wide a coverage of modern nonparametric methods ... . the key ideas and basic proofs are carefully explained. Bibliographic remarks point the reader to references that contain further details. Each chapter is finished with useful exercises ... . The book is also suitable for researchers in statistics, machine learning, and data mining." (Oleksandr Kukush, Zentralblatt MATH, Vol. 1099 (1), 2007)

"Sobre este título" puede pertenecer a otra edición de este libro.

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Larry Wasserman
Editorial: Springer-Verlag New York Inc., United States (2010)
ISBN 10: 1441920447 ISBN 13: 9781441920447
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Descripción Springer-Verlag New York Inc., United States, 2010. Paperback. Estado de conservación: New. 1st ed. Softcover of orig. ed. 2006. Language: English . Brand New Book ***** Print on Demand *****.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. Nº de ref. de la librería AAV9781441920447

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Descripción Springer-Verlag New York Inc., United States, 2010. Paperback. Estado de conservación: New. 1st ed. Softcover of orig. ed. 2006. Language: English . Brand New Book ***** Print on Demand *****. 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. Nº de ref. de la librería AAV9781441920447

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Descripción Springer-Verlag New York Inc., United States, 2010. Paperback. Estado de conservación: New. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. 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. Softcover reprint of hardcover 1st ed. 2006. Nº de ref. de la librería LIE9781441920447

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Descripción Springer-Verlag New York Inc., 2010. PAP. Estado de conservación: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería IP-9781441920447

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Descripción Springer-Verlag New York Inc., 2010. PAP. Estado de conservación: New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000. Nº de ref. de la librería IP-9781441920447

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Descripción Springer New York 2010-11-19, New York |London, 2010. paperback. Estado de conservación: New. Nº de ref. de la librería 9781441920447

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Descripción Springer, 2010. Paperback. Estado de conservación: NEW. 9781441920447 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Nº de ref. de la librería HTANDREE0294884

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Descripción Springer Nov 2010, 2010. Taschenbuch. Estado de conservación: Neu. Neuware - 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. 284 pp. Englisch. Nº de ref. de la librería 9781441920447

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Descripción Springer, 2010. Paperback. Estado de conservación: New. This item is printed on demand. Nº de ref. de la librería DADAX1441920447

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