All of Nonparametric Statistics

All of Nonparametric Statistics

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.

• Introduction.
• Estimating the CDF and Statistical Functions.
• 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 Means.

Infotext:

There are many books on various aspects of nonparametric inference but no other book covers all the topics in one place

• Statistische Theorie und Methoden
• Künstliche Intelligenz (einschl. Roboter)
• Statistik in Technik, Physik, Informatik, Chemie und Geowissenschaften