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Information theory and the central limit theorem /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London : River Edge, NJ :
Imperial College Press ; Distributed by World Scientific Pub.,
©2004.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Johnson, Oliver |q (Oliver Thomas), |e author. | |
| 245 | 1 | 0 | |a Information theory and the central limit theorem / |c Oliver Johnson. |
| 260 | |a London : |b Imperial College Press ; |a River Edge, NJ : |b Distributed by World Scientific Pub., |c ©2004. | ||
| 300 | |a 1 online resource (xiv, 209 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a data file | ||
| 504 | |a Includes bibliographical references (pages 199-206) and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a 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. | |
| 520 | |a 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 It brings together results from a number of research papers as well as unpublished material, showing how the techniques can give a unified view of limit theorems. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Central limit theorem. | |
| 650 | 0 | |a Information theory |x Statistical methods. | |
| 650 | 0 | |a Probabilities. | |
| 650 | 2 | |a Probability | |
| 650 | 6 | |a Théorème central limite. | |
| 650 | 6 | |a Théorie de l'information |x Méthodes statistiques. | |
| 650 | 6 | |a Probabilités. | |
| 650 | 7 | |a probability. |2 aat | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 7 | |a Central limit theorem. |2 fast |0 (OCoLC)fst00850721 | |
| 650 | 7 | |a Information theory |x Statistical methods. |2 fast |0 (OCoLC)fst00973161 | |
| 650 | 7 | |a Probabilities. |2 fast |0 (OCoLC)fst01077737 | |
| 776 | 0 | 8 | |i Print version: |a Johnson, Oliver (Oliver Thomas). |t Information theory and the central limit theorem. |d London : Imperial College Press ; River Edge, NJ : Distributed by World Scientific Pub., ©2004 |z 1860944736 |w (OCoLC)56905822 |
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