Authors:
- There are many books on various aspects of nonparametric inference but no other book covers all the topics in one place
- Offers a brief account of the modern topics in nonparametric inference
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Texts in Statistics (STS)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
About this book
Reviews
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 containfurther 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)
Authors and Affiliations
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Department of Statistics, Carnegie Mellon University, Pittsburgh, USA
Larry Wasserman
Bibliographic Information
Book Title: All of Nonparametric Statistics
Authors: Larry Wasserman
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/0-387-30623-4
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag New York 2006
Hardcover ISBN: 978-0-387-25145-5Published: 21 October 2005
Softcover ISBN: 978-1-4419-2044-7Published: 19 November 2010
eBook ISBN: 978-0-387-30623-0Published: 10 September 2006
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 1
Number of Pages: XII, 270
Topics: Statistical Theory and Methods, Artificial Intelligence, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences