Nonparametric Tests for Complete Data

ISBN-13: 9781848212695 / Angielski / Twarda / 2011 / 320 str.

Vilijandas Bagdonavi?us; Julius Kruopis; Mikhail Nikulin

Opis

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.

Spis treści

Preface xi

Terms and Notation xv

Chapter 1. Introduction 1

1.1. Statistical hypotheses 1

1.2. Examples of hypotheses in non–parametric models 2

1.3. Statistical tests 5

1.4. P–value 7

1.5. Continuity correction 10

1.6. Asymptotic relative efficiency 13

Chapter 2. Chi–squared Tests 17

2.1. Introduction 17

2.2. Pearson s goodness–of–fit test: simple hypothesis 17

2.3. Pearson s goodness–of–fit test: composite hypothesis 26

2.4. Modified chi–squared test for composite hypotheses 34

2.5. Chi–squared test for independence 52

2.6. Chi–squared test for homogeneity 57

2.7. Bibliographic notes 64

2.8. Exercises 64

2.9. Answers 72

Chapter 3. Goodness–of–fit Tests Based on Empirical Processes 77

3.1. Test statistics based on the empirical process 77

3.2. Kolmogorov Smirnov test 82

3.3. 2, Cramér von–Mises and Andersen Darling tests 86

3.4. Modifications of Kolmogorov Smirnov, Cramér von–Mises and Andersen Darling tests: composite
hypotheses 91

3.5. Two–sample tests 98

3.6. Bibliographic notes 104

3.7. Exercises106

3.8. Answers 109

Chapter 4. Rank Tests 111

4.1. Introduction 111

4.2. Ranks and their properties 112

4.3. Rank tests for independence 117

4.4. Randomness tests 139

4.5. Rank homogeneity tests for two independent samples 146

4.6. Hypothesis on median value: the Wilcoxon signed ranks test 168

4.7. Wilcoxon s signed ranks test for homogeneity of two related samples 180

4.8. Test for homogeneity of several independent samples: Kruskal Wallis test 181

4.9. Homogeneity hypotheses for k related samples: Friedman test 191

4.10. Independence test based on Kendall s concordance coefficient  204

4.11. Bibliographic notes 208

4.12. Exercises 209

4.13. Answers 212

Chapter 5. Other Non–parametric Tests 215

5.1. Sign test 215

5.2. Runs test 221

5.3. McNemar s test 231

5.4. Cochran test 238

5.5. Special goodness–of–fit tests 245

5.6. Bibliographic notes 268

5.7. Exercises 269

5.8. Answers 271

APPENDICES 275

Appendix A. Parametric Maximum Likelihood 277

Appendix B. Notions from the Theory of 281

BBibliography 293

Index 305