Statistical inference. 2nd ed

This edition of Statistical Inference is similar in nature to the original from 1995, see Zbl 0862.62002, with additional material on estimating equations, local likelihood and fiducial intervals. The sections on Gibbs sampling, generalized linear models, tests based on ranks and the bootstrap have been substantially revised. The book is easy to read and is designed to be an advanced level textbook for senior undergraduate students. There is a collection of exercises associated with each chapter. The book is also a useful, comprehensive reference for practising statisticians. Contents: 1. Introduction; 2. Properties of estimators; 3. Maximum likelihood and other methods of estimation; 4. Hypothesis testing; 5. Interval estimation; 6. The decision-theory approach to inference; 7. Bayesian inference; 8. Nonparametric and robust inference; 9. Computationally intensive methods; 10. Generalized linear models.