Asymptotic Theory of Statistics and Probability

Authors:

ISBN: 978-0-387-75970-8 (Print) 978-0-387-75971-5 (Online)

Table of contents (35 chapters)

previous Page of 2
  1. Front Matter

    Pages I-XXVII

  2. Chapter

    Pages 1-17

    Basic Convergence Concepts and Theorems

  3. Chapter

    Pages 19-34

    Metrics, Information Theory, Convergence, and Poisson Approximations

  4. Chapter

    Pages 35-47

    More General Weak and Strong Laws and the Delta Theorem

  5. Chapter

    Pages 49-61

    Transformations

  6. Chapter

    Pages 63-81

    More General Central Limit Theorems

  7. Chapter

    Pages 83-89

    Moment Convergence and Uniform Integrability

  8. Chapter

    Pages 91-100

    Sample Percentiles and Order Statistics

  9. Chapter

    Pages 101-117

    Sample Extremes

  10. Chapter

    Pages 119-129

    Central Limit Theorems for Dependent Sequences

  11. Chapter

    Pages 131-140

    Central Limit Theorem for Markov Chains

  12. Chapter

    Pages 141-149

    Accuracy of Central Limit Theorems

  13. Chapter

    Pages 151-183

    Invariance Principles

  14. Chapter

    Pages 185-201

    Edgeworth Expansions and Cumulants

  15. Chapter

    Pages 203-224

    Saddlepoint Approximations

  16. Chapter

    Pages 225-234

    U-statistics

  17. Chapter

    Pages 235-258

    Maximum Likelihood Estimates

  18. Chapter

    Pages 259-269

    M Estimates

  19. Chapter

    Pages 271-278

    The Trimmed Mean

  20. Chapter

    Pages 279-288

    Multivariate Location Parameter and Multivariate Medians

  21. Chapter

    Pages 289-321

    Bayes Procedures and Posterior Distributions

previous Page of 2