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

• Autore: Johnson Oliver (Oliver Thomas)
• Pubblicazione: London, : Imperial College Press; River Edge, NJ, : Distributed by World Scientific Publishing, c2004
• Descrizione fisica: 1 online resource (224 p.)
• Disciplina: 519.2
• Soggetto topico: Central limit theorem; Information theory - Statistical methods; Probabilities
• 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 It brings together results from a number of research papers as well as unpublished material, showing how the techniques can give a unified view of limit theorems.
• Titolo autorizzato: Information theory and the central limit theorem
• ISBN: 1-281-86643-1; 9786611866433; 1-86094-537-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910783482803321
• Lo trovi qui: Univ. Federico II