Key features include:
- A unified approach to statistical estimation emphasising the analogy (or bootstrap) principle
- An introduction to bootstrap and jackknife methods for assessing the accuracy of an estimator
- Detailed discussion of nonparametric methods for estimating density and regression functions
- Emphasis on diagnostic procedures and on prediction criteria for evaluating the results of statistical analysis
- An introduction to linear exponential family and generalized linear models
- A thorough discussion of robustness in statistical sense.