Non-parametric Tests for Complete Data: Bagdonavičius/Non-parametric Tests for Complete Data

This book concerns testing hypotheses in non-parametric models. Classical non-parametric tests (goodness-of-fit, homogeneity, randomness, independence) of complete data are considered. Most of the test results are proved and real applications are illustrated using examples. Theories and exercises are provided. The incorrect use of many tests applying most statistical software is highlighted and discussed. Content: Chapter 1 Introduction (pages 1–16): Chapter 2 Chi?Squared Tests (pages 17–75): Chapter 3 Goodness?of?fit Tests Based on Empirical Processes (pages 77–110): Chapter 4 Rank Tests (pages 111–214): Chapter 5 Other Non?parametric Tests (pages 215–273): Chapter A Parametric Maximum Likelihood Estimators (pages 275–280): Chapter B Notions from the Theory of Stochastic Processes (pages 281–292):