Summaries and Customer Reviews are supplied by Amazon.com

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.

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, Vol. 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, Vol. 49, No. 1., February 2007)

Average Customer Rating:

I don't think it is quite all of nonparametrics but good topics well presented in brief

Customer Rating:

This is a very nice and concisely written account of the field of nonparametrics. It is very bold for an athor to use "all" in the title nad I am sure that Wasserman does this with tongue in cheek. He has been even bolder with his other book called "All of Statistics." However I think that it can safely be said that the essentials are covered along with many interesting topic that are not covered in a traditional nonparametrics text such as Conover's book. The author's intentions are best expressed in this excerpt from the publisher's description. "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." So we see that by "all" the author means a brief description of most topics in nonparametrics. Nonparametric density estimation, bootstrap, nonparametric regression, and wavelets are not covered in traditional nonparametric books and the topics are so involved that each has been treated in books solely dedicated to that topic. I and at least five other authors have written books dedicated to the bootstrap and other resampling methods. Hardle and others have written books on nonparametic regression and Silverman and others have puvlished books on univariate nonparametric density estimation. Scott has done one on multivariate nonparametric density estimation. The topics are impressive and the coverage is good but obviously not thorough. To thoroughly treat alll these topics would take several thousands of pages!

10-to-1 Equation to Text Ratio

Customer Rating:

My first thought upon receiving this slim volume went something along the lines of "Oh my, all of non-parametric statistics is much, much smaller than I expected". My other impressions are somewhat vague since (as the title of this review implies), this is not exactly a flip-through book for light reading. The content is dense ... like 100-year old ebony wood. And after carefully examining the table of contents, I also noticed that the text has precious little to say about methods based on rank. So this is more or less a book on "modern methods". It's a very interesting selection of material - although I will probably never be able to read it.