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Springer All of Nonparametric Statistics - Text Book

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Description

All of Nonparametric Statistics from the Springer Texts in Statistics series provides a comprehensive resource for modern nonparametric inference. While many books focus on specific areas like density estimation, nonparametric regression, bootstrapping, or wavelet methods, this text brings these diverse topics together in one location. Designed for academic and professional use, this book offers a brief account of many modern topics in the field. It serves as an essential tool for master's-level or Ph.D.-level students in statistics and computer science. Additionally, it is a practical resource for researchers in machine learning, data mining, and statistics who need to quickly get up to speed on modern nonparametric methods.

Key Features

This Springer textbook provides a single location to study various topics in nonparametric inference.

The content covers essential modern topics including density estimation, bootstrapping, and wavelet methods.

Designed specifically for master's-level and Ph.D.-level statistics and computer science students.

Serves as a fast-paced resource for researchers in machine learning and data mining.

Part of the professional Springer Texts in Statistics series for academic excellence.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
21 October 2005
Listed Since
22 January 2007

Barcode

No barcode data available

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