Mathematical statistics : basic ideas and selected topics / Peter. J. Bickel and Kjell A. Doksum.

Vol. 2 has no edition statement.

Includes bibliographical references and index.

vol. 1.
1. Statistical models, goals, and performance criteria --
2. Methods of estimation --
3. Measures of performance --
4. Testing and confidence regions --
5. Asymptotic approximations --
6. Inference in the multiparameter case --
A. A review of basic probability theory --
B. Additional topics in probability and analysis --
C. Tables --
vol. 2.
7. Tools for asymptotic analysis --
8. Distribution-free, unbiased, and equivalent procedures --
9. Inference in semiparametric models --
10. Monte Carlo methods --
11. Nonparametric inference for functions of one variable --
12. Prediction and machine learning --
D. Appendix D. Supplements to text --
E. Solutions for volume II.

Volume I presents fundamental, classical statistical concepts at the doctorate level without using measure theory. It gives careful proofs of major results and explains how the theory sheds light on the properties of practical methods.
Volume II covers a number of topics that are important in current measure theory and practice. It emphasizes nonparametric methods which can really only be implemented with modern computing power on large and complex data sets. In addition, the set includes a large number of problems with more difficult ones appearing with hints and partial solutions for the instructor.