1.

Record Nr.

UNINA9910783482803321

Autore

Johnson Oliver (Oliver Thomas)

Titolo

Information theory and the central limit theorem [[electronic resource] /] / Oliver Johnson

Pubbl/distr/stampa

London, : Imperial College Press

River Edge, NJ, : Distributed by World Scientific Publishing, c2004

ISBN

1-281-86643-1

9786611866433

1-86094-537-6

Descrizione fisica

1 online resource (224 p.)

Disciplina

519.2

Soggetti

Central limit theorem

Information theory - Statistical methods

Probabilities

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. 199-206) and index.

Nota di contenuto

Information Theory and The Central Limit Theorem; Preface; Contents; 1. Introduction to Information Theory; 2. Convergence in Relative Entropy; 3. Non-Identical Variables and Random Vectors; 4. Dependent Random Variables; 5. Convergence to Stable Laws; 6. Convergence on Compact Groups; 7. Convergence to the Poisson Distribution; 8. Free Random Variables; Appendix A Calculating Entropies; Appendix B Poincare Inequalities; Appendix C de Bruijn Identity; Appendix D Entropy Power Inequality; Appendix E Relationships Between Different Forms of Convergence; Bibliography; Index

Sommario/riassunto

This book provides a comprehensive description of a new method of proving the central limit theorem, through the use of apparently unrelated results from information theory. It gives a basic introduction to the concepts of entropy and Fisher information, and collects together standard results concerning their behaviour. It brings together results from a number of research papers as well as unpublished material, showing how the techniques can give a unified view of limit theorems.