Rissanen Information and Complexity in Statistical Modeling

1. Auflage 2007
ISBN: 978-0-387-68812-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 142 Seiten

Reihe: Information Science and Statistics

No statistical model is 'true' or 'false,' 'right' or 'wrong'; the models just have varying performance, which can be assessed. The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling. Although the prerequisites include only basic probability calculus and statistics, a moderate level of mathematical proficiency would be beneficial.

Autoren/Hrsg.

Rissanen, Jorma

Inhaltsverzeichnis

1;Contents;5
2;Preface;7
3;Introduction;9
4;Part I Information and Coding;15
4.1;Shannon— Wiener Information;17
4.2;Coding of Random Processes;35
5;Part II Statistical Modeling;50
5.1;Kolmogorov Complexity;53
5.2;Stochastic Complexity;63
5.3;Structure Function;84
5.4;Optimally Distinguishable Models;93
5.5;The MDL Principle;100
5.6;Applications;106
6;References;137
7;Index;142