LEADER 02956nam 2200613Ia 450 001 9910450231003321 005 20200520144314.0 010 $a1-281-86643-1 010 $a9786611866433 010 $a1-86094-537-6 035 $a(CKB)1000000000032783 035 $a(EBL)231540 035 $a(OCoLC)475937135 035 $a(SSID)ssj0000179228 035 $a(PQKBManifestationID)11184083 035 $a(PQKBTitleCode)TC0000179228 035 $a(PQKBWorkID)10229943 035 $a(PQKB)11773761 035 $a(MiAaPQ)EBC231540 035 $a(WSP)0000P341 035 $a(Au-PeEL)EBL231540 035 $a(CaPaEBR)ebr10082185 035 $a(CaONFJC)MIL186643 035 $a(EXLCZ)991000000000032783 100 $a20041104d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aInformation theory and the central limit theorem$b[electronic resource] /$fOliver Johnson 210 $aLondon $cImperial College Press ;$aRiver Edge, NJ $cDistributed by World Scientific Publishing$dc2004 215 $a1 online resource (224 p.) 300 $aDescription based upon print version of record. 311 $a1-86094-473-6 320 $aIncludes bibliographical references (p. 199-206) and index. 327 $aInformation 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 330 $aThis 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 It brings together results from a number of research papers as well as unpublished material, showing how the techniques can give a unified view of limit theorems. 606 $aCentral limit theorem 606 $aInformation theory$xStatistical methods 606 $aProbabilities 608 $aElectronic books. 615 0$aCentral limit theorem. 615 0$aInformation theory$xStatistical methods. 615 0$aProbabilities. 676 $a519.2 700 $aJohnson$b Oliver$g(Oliver Thomas)$0160688 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910450231003321 996 $aInformation theory and the central limit theorem$91020297 997 $aUNINA