A comprehensive and consistent theory of estimation, including a description of a powerful new tool, the generalized maximum capacity estimator.
This book presents a comprehensive and consistent theory of estimation. The framework described leads naturally to a powerful new tool, the generalized maximum capacity estimator. This approach allows the optimal estimation of real-valued parameters, their number and intervals, and provides common ground for explaining the power of these estimators.
1. Introduction; 2. Coding; 3. Basics of information; 4. Modeling problem; 5. Other optimality properties; 6. Interval estimation; 7. Hypothesis testing; 8. Denoising; 9. Sequential models; Appendix A. Elements of algorithmic information; Appendix B. Universal prior for integers.