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All of Nonparametric Statistics

โœ Scribed by Larry Wasserman

Tongue
English
Leaves
272
Series
Springer Texts in Statistics
Category
Library
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โœฆ Synopsis

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 bookโ€™s dual approach includes a mixture of methodology and theory.

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[Updated: Aug 17th. After this update, I would downgrade this book to 3 stars, which is still "good" under my rating system.]I've read about 75% of this book, quitting near the end where the material was of less interest to me. I found this book to be largely focused the theory of nonparametrics wit