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Record Nr. |
UNINA9910783482803321 |
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Autore |
Johnson Oliver (Oliver Thomas) |
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Titolo |
Information theory and the central limit theorem [[electronic resource] /] / Oliver Johnson |
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Pubbl/distr/stampa |
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London, : Imperial College Press |
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River Edge, NJ, : Distributed by World Scientific Publishing, c2004 |
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ISBN |
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1-281-86643-1 |
9786611866433 |
1-86094-537-6 |
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Descrizione fisica |
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1 online resource (224 p.) |
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Disciplina |
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Soggetti |
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Central limit theorem |
Information theory - Statistical methods |
Probabilities |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references (p. 199-206) and index. |
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Nota di contenuto |
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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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Sommario/riassunto |
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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 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. |
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