All of nonparametric statistics
著者
書誌事項
All of nonparametric statistics
（Springer texts in statistics）
Springer, c2006
- : softcover
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注記
Includes bibliographical references (p. [243]-257) and index
Softcover reprint of the hardcover 1st edition 2006
内容説明・目次
内容説明
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.
目次
Estimating the CDF and Statistical Functionals.- The Bootstrap and the Jackknife.- Smoothing: General Concepts.- Nonparametric Regression.- Density Estimation.- Normal Means and Minimax Theory.- Nonparametric Inference Using Orthogonal Functions.- Wavelets and Other Adaptive Methods.- Other Topics.
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