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About this product
- DescriptionThis text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nparametric 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 nparametric methods. It covers a wide range of topics including the bootstrap, the nparametric delta method, nparametric regression, density estimation, orthogonal function methods, minimax estimation, nparametric confidence sets, and wavelets. The book's dual approach includes a mixture of methodology and theory.
- Author(s)Larry Wasserman
- PublisherSpringer-Verlag New York Inc.
- Date of Publication18/11/2010
- SubjectScience & Mathematics: Textbooks & Study Guides
- Series TitleSpringer Texts in Statistics
- Place of PublicationNew York, NY
- Country of PublicationUnited States
- ImprintSpringer-Verlag New York Inc.
- Content Note52 black & white illustrations
- Weight439 g
- Width155 mm
- Height235 mm
- Spine15 mm
- Edition Statement1st ed. Softcover of orig. ed. 2006
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