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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)

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I may never finish a proper review. So let me at least present the Table of Contents and a quick guide for Philosophers of Science. The non-technical chapters are rich with new (or uncommon) insights about Induction, Explanation, Theory Choice, and even the Arrow of Time.

Table of Contents
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1. Inductive Inference
2. Information
3. Strict Minimum Message Length (SMML)
4. Approximations to SMML
5. MML: Quadratic Approximations to SMML
6. MML Details in Some Interesting Cases
7. Structural Models
8. The Feathers on the Arrow of Time
9. MML as a Descriptive Theory
10. Related Word

Philosophers of Science should read:
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* Chapter 1, at least through 1.5 (18 pages).
- - MML as a precise rendering of Occam's Razor
- - Why the best explanation is the shortest
- - MML as induction (pure Bayesianism as deductive)
- - MML explanations, induction, unification, etc.
* Chapter 9 (12 pages)
- - The big picture: can you use MML to describe scientific revolutions?

Those interested in the Arrow of Time should read
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* Chapter 8 (38 pages)
- - A very careful account of reversibility and irreversibility.
- - Accurate simulations to convince people not already convinced of Boltzmann's claim that entropy will increase in both directions.
- - A novel account of asymmetry, suggesting that while we predict the future, we EXPLAIN the past, in the MML sense. That is, MML inference naturally picks out the past we remember, as it is the best explanation of the present.

Anyone wanting more details should begin with:
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* Chapter 2 (87 pages)
- - Shannon Information, coding, and entropy
- - Algorithmic Complexity
- - Information, Inference, and Explanation