Statistical Tests Of Nonparametric Hypotheses: Asymptotic Theory, 1st Edition

  • Published By: World Scientific Publishing Company
  • ISBN-10: 9814531758
  • ISBN-13: 9789814531757
  • DDC: 519.5
  • Grade Level Range: College Freshman - College Senior
  • 304 Pages | eBook
  • Original Copyright 2013 | Published/Released January 2015
  • This publication's content originally published in print form: 2013

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An overview of the asymptotic theory of optimal nonparametric tests is presented in this book. It covers a wide range of topics: Neyman-Pearson and LeCams theories of optimal tests, the theories of empirical processes and kernel estimators with extensions of their applications to the asymptotic behavior of tests for distribution functions, densities and curves of the nonparametric models defining the distributions of point processes and diffusions. With many new test statistics developed for smooth curves, the reliance on kernel estimators with bias corrections and the weak convergence of the estimators are useful to prove the asymptotic properties of the tests, extending the coverage to semiparametric models. They include tests built from continuously observed processes and observations with cumulative intervals.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
1: Introduction.
2: Asymptotic Theory.
3: Nonparametric Tests for One Sample.
4: Two-Sample Tests.
5: Multi-Dimensional Tests.
6: Nonparametric Tests for Processes.
7: Nonparametric Tests under Censoring or Truncation.
8: Sequential Tests.
Functional Estimation and Probability.