Information theory and the central limit theorem /

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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 concer...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Johnson, Oliver (Oliver Thomas) (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : River Edge, NJ : Imperial College Press ; Distributed by World Scientific Pub., ©2004.
Temas:
Central limit theorem.
Information theory > Statistical methods.
Probabilities.
Probability
Théorème central limite.
Théorie de l'information > Méthodes statistiques.
Probabilités.
probability.
MATHEMATICS > Probability & Statistics > General.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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.

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