Applied Asymptotics
Applied Asymptotics
A. C. Davison, École Polytechnique Fédérale de Lausanne
N. Reid, University of Toronto
$101.00
USDIn 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. Author resource page: http://www.isib.cnr.it/~brazzale/AA/ <a href=" http://www.isib.cnr.it/~brazzale/AA/"></a>
- First practical treatment of small-sample asymptotics
- Clearly illustrates the use and effect of new likelihood-based methods with realistic examples and case studies
- Accompanied by code in the R language (available online), allowing practitioners to apply the methods to a wide range of situations
Reviews & endorsements
"A solid and useful contribution to applied statistics. Students of statistics and practicing statisticians will find much to study and learn here."
Andrew Robinson, University of Melbourne
"I highly recommend the book to researchers looking for ways to improve accuracy in statistical testing. The book is well written, the examples are clear, and because all examples can be verified by the reader through the provided packages and code in R, the analyses can be explored in great detail."
Lourens Waldrop, Biometrics
Product details
July 2007Hardback
9780521847032
248 pages
260 × 185 × 18 mm
0.604kg
49 b/w illus. 47 tables 69 exercises
Available
Table of Contents
- 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.
