Applied asymptotics : case studies in small-sample statistics
著者
書誌事項
Applied asymptotics : case studies in small-sample statistics
（Cambridge series on statistical and probabilistic mathematics）
Cambridge University Press, 2007
大学図書館所蔵 件 / 全13件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references (p. [219]-228) and index
内容説明・目次
内容説明
In fields such as biology, medical sciences, sociology, and economics researchers often face the situation where the number of available observations, or the amount of available information, is sufficiently small that approximations based on the normal distribution may be unreliable. Theoretical work over the last quarter-century has led to new likelihood-based methods that lead to very accurate approximations in finite samples, but this work has had limited impact on statistical practice. This book illustrates by means of realistic examples and case studies how to use the new theory, and investigates how and when it makes a difference to the resulting inference. The treatment is oriented towards practice and comes with code in the R language (available from the web) which enables the methods to be applied in a range of situations of interest to practitioners. The analysis includes some comparisons of higher order likelihood inference with bootstrap or Bayesian methods.
目次
- Preface
- 1. Introduction
- 2. Uncertainty and approximation
- 3. Simple illustrations
- 4. Discrete data
- 5. Regression with continuous responses
- 6. Some case studies
- 7. Further topics
- 8. Likelihood approximations
- 9. Numerical implementation
- 10. Problems and further results
- Appendices - some numerical techniques: Appendix 1. Convergence of sequences
- Appendix 2. The sample mean
- Appendix 3. Laplace approximation
- Appendix 4. X2 approximations
- Bibliography
- Index.
「Nielsen BookData」 より