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Testing Hypotheses for a Single Parameter

  • Bing LiEmail author
  • G. Jogesh Babu
Chapter
  • 2k Downloads
Part of the Springer Texts in Statistics book series (STS)

Abstract

Basic concepts of hypothesis testing are presented in this Chapter. The Neyman-Pearson Lemma, which gives the form of the Most Powerful test for simple hypotheses, is introduced. This is then used as the building block for constructing the Uniformly Most Powerful tests and the Uniformly Most Powerful Unbiased tests. In this connection, special assumptions on the forms of the distribution of the data, such as the Monotone Likelihood Ratio, are presented. The focus is on testing of a scalar parameter.

References

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of StatisticsPenn State UniversityUniversity ParkUSA

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