This textbook provides a self-contained presentation of the main concepts and methods of nonparametric statistical testing, with a particular focus on the theoretical foundations of goodness-of-fit tests, rank tests, resampling tests, and projection tests. The substitution principle is employed as a unified approach to the nonparametric test problems discussed. In addition to mathematical theory, it also includes numerous examples and computer implementations. The book is intended for advanced undergraduate, graduate, and postdoc students as well as young researchers. Readers should be familiar with the basic concepts of mathematical statistics typically covered in introductory statistics courses.
|Publisher:||Springer International Publishing|
|Edition description:||Softcover reprint of the original 1st ed. 2018|
|Product dimensions:||6.10(w) x 9.25(h) x (d)|
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Table of ContentsIntroduction and Examples.- Empirical Measure, Empirical Processes.- Goodness-of-fit Tests.- Rank Tests.- Asymptotics of Linear Resampling Statistics.- Bootstrap Methods for Linear Models.- Projection Tests.- Some Extensions.