LEADER 03880nam 22006614a 450 001 9910778260503321 005 20230828204700.0 010 $a1-281-92454-7 010 $a9786611924546 010 $a981-277-299-5 035 $a(CKB)1000000000480147 035 $a(EBL)1681549 035 $a(OCoLC)820942654 035 $a(SSID)ssj0000140166 035 $a(PQKBManifestationID)11163012 035 $a(PQKBTitleCode)TC0000140166 035 $a(PQKBWorkID)10029374 035 $a(PQKB)11315172 035 $a(MiAaPQ)EBC1681549 035 $a(WSP)00006189 035 $a(Au-PeEL)EBL1681549 035 $a(CaPaEBR)ebr10201346 035 $a(CaONFJC)MIL192454 035 $a(EXLCZ)991000000000480147 100 $a20060601d2006 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aDistribution models theory$b[electronic resource] /$feditors Rafael Herreri?as Pleguezuelo, Jose? Callejo?n Ce?spedes, and Jose? Manual Herreri?as Velasco 210 $aNew Jersey $cWorld Scientific$dc2006 215 $a1 online resource (307 p.) 300 $aDescription based upon print version of record. 311 $a981-256-900-6 320 $aIncludes bibliographical references. 327 $aContents; Preface; Chapter 1 Modeling Income Distributions Using Elevated Distributions on a Bounded Domain; 1. Introduction; 2. Cumulative distribution function and density function; 3. Properties of Standard RGTL distributions; 4. Maximum likelihood estimation 327 $a5. Fitting 2001 U.S. income distribution data 6. Concluding remarks; Acknowledgments; References; Chapter 2 Making Copulas Under Uncertainty; 1. Introduction; 2. Initial approach; 3. FGM distribution functions; 4. The Dorp and Kotz's distribution families and its subfamilies 327 $a5. An approach to the problem: Application of the MTDF with van Dorp and Kotz's marginals in an uncertainty environment 6. A solution; 7. A valuation method; 8. Practical application of the MTDF with van Dorp and Kotz's marginals under uncertainty environment; 9. Conclusions 327 $aReferences Chapter 3 Valuation Method of the Two Survival Functions; 1. Introduction; 2. Valuation method of the two survival functions; 3. VMTS from a multidimensional quality index; 4. Practical application; 5. Conclusions; References 327 $aChapter 4 Weighting Tools and Alternative Techniques to Generate Weighted Probability Models in Valuation Theory 1. Introduction; 2. Techniques to generate weighted models valuation; 3. New technique to generate weighted models ; 4. Practical application; 5. Comments and conclusions 327 $aReferences 330 $aDistribution Models Theory is a revised edition of papers specially selected by the Scientific Committee for the Fifth Workshop of Spanish Scientific Association of Applied Economy on Distribution Models Theory held in Granada (Spain) in September 2005. The contributions offer a must-have point of reference on models theory. This book has been selected for coverage in: Index to Scientific & Technical Proceedings® (ISTP®/ISI Proceedings) Index to Scientific & Technical Proceedings (ISTP CDROM version/ISI Proceedings) Sample Chapter(s)
Chapter 1: Modeling Income Distributions 606 $aModel theory 606 $aDistribution (Probability theory) 615 0$aModel theory. 615 0$aDistribution (Probability theory) 676 $a511.3/4 701 $aHerreri?as-Pleguezuelo$b Rafael$01492819 701 $aCallejo?n-Ce?spedes$b Jose?$01492820 701 $aHerreri?as--Velasco$b Jose? Manual$01492821 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910778260503321 996 $aDistribution models theory$93715530 997 $aUNINA