LEADER 02170nam 22004335a 450 001 9910151934803321 005 20091109150325.0 010 $a3-03719-563-0 024 70$a10.4171/063 035 $a(CKB)3710000000953827 035 $a(CH-001817-3)12-091109 035 $a(PPN)178155438 035 $a(EXLCZ)993710000000953827 100 $a20091109j20080626 fy 0 101 0 $aeng 135 $aurnn|mmmmamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFukaya Categories and Picard-Lefschetz Theory$b[electronic resource] /$fPaul Seidel 210 3 $aZuerich, Switzerland $cEuropean Mathematical Society Publishing House$d2008 215 $a1 online resource (334 pages) 225 0 $aZurich Lectures in Advanced Mathematics (ZLAM) 330 $aThe central objects in the book are Lagrangian submanifolds and their invariants, such as Floer homology and its multiplicative structures, which together constitute the Fukaya category. The relevant aspects of pseudo-holomorphic curve theory are covered in some detail, and there is also a self-contained account of the necessary homological algebra. Generally, the emphasis is on simplicity rather than generality. The last part discusses applications to Lefschetz fibrations, and contains many previously unpublished results. The book will be of interest to graduate students and researchers in symplectic geometry and mirror symmetry. Winner 2010 AMS Veblen Prize in Geometry. 606 $aDifferential & Riemannian geometry$2bicssc 606 $aDifferential geometry$2msc 606 $aAssociative rings and algebras$2msc 606 $aSeveral complex variables and analytic spaces$2msc 615 07$aDifferential & Riemannian geometry 615 07$aDifferential geometry 615 07$aAssociative rings and algebras 615 07$aSeveral complex variables and analytic spaces 686 $a53-xx$a16-xx$a32-xx$2msc 700 $aSeidel$b Paul$01070777 801 0$bch0018173 906 $aBOOK 912 $a9910151934803321 996 $aFukaya Categories and Picard-Lefschetz Theory$92565020 997 $aUNINA LEADER 03774nam 2200637 a 450 001 9910788555203321 005 20230725045527.0 010 $a1-283-14441-7 010 $a9786613144416 010 $a981-4299-88-X 035 $a(CKB)3360000000001365 035 $a(EBL)731162 035 $a(OCoLC)741492811 035 $a(SSID)ssj0000634096 035 $a(PQKBManifestationID)12207111 035 $a(PQKBTitleCode)TC0000634096 035 $a(PQKBWorkID)10622242 035 $a(PQKB)11008330 035 $a(MiAaPQ)EBC731162 035 $a(WSP)00007699 035 $a(Au-PeEL)EBL731162 035 $a(CaPaEBR)ebr10480285 035 $a(CaONFJC)MIL314441 035 $a(EXLCZ)993360000000001365 100 $a20110712d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aDependence modeling$b[electronic resource] $evine copula handbook /$feditors, Dorota Kurowicka, Harry Joe 210 $aHackensack, N.J. $cWorld Scientific$d2011 215 $a1 online resource (368 p.) 300 $aDescription based upon print version of record. 311 $a981-4299-87-1 320 $aIncludes bibliographical references and index. 327 $aPreface; Contents; 1. Introduction: Dependence Modeling D. Kurowicka; 2. Multivariate Copulae M. Fischer; 3. Vines Arise R. M. Cooke, H. Joe and K. Aas; 4. Sampling Count Variables with Specified Pearson Correlation: A Comparison between a Naive and a C-Vine Sampling Approach V. Erhardt and C. Czado; 5. Micro Correlations and Tail Dependence R. M. Cooke, C. Kousky and H. Joe; 6. The Copula Information Criterion and Its Implications for the Maximum Pseudo-Likelihood Estimator S. Grønneberg; 7. Dependence Comparisons of Vine Copulae with Four or More Variables H. Joe 327 $a8. Tail Dependence in Vine Copulae H. Joe9. Counting Vines O. Morales-Napoles; 10. Regular Vines: Generation Algorithm and Number of Equivalence Classes H. Joe, R. M. Cooke and D. Kurowicka; 11. Optimal Truncation of Vines D. Kurowicka; 12. Bayesian Inference for D-Vines: Estimation and Model Selection C. Czado and A. Min; 13. Analysis of Australian Electricity Loads Using Joint Bayesian Inference of D-Vines with Autoregressive Margins C. Czado, F. G ?artner and A. Min; 14. Non-Parametric Bayesian Belief Nets versus Vines A. Hanea 327 $a15. Modeling Dependence between Financial Returns Using Pair-Copula Constructions K. Aas and D. Berg16. Dynamic D-Vine Model A. Heinen and A. Valdesogo; 17. Summary and Future Directions D. Kurowicka; Index 330 $aThis book is a collaborative effort from three workshops held over the last three years, all involving principal contributors to the vine-copula methodology. Research and applications in vines have been growing rapidly and there is now a growing need to collate basic results, and standardize terminology and methods. Specifically, this handbook will trace historical developments, standardizing notation and terminology, summarize results on bivariate copulae, summarize results for regular vines, and give an overview of its applications. In addition, many of these results are new and not readily 606 $aCopulas (Mathematical statistics) 606 $aDependence (Statistics) 606 $aDistribution (Probability theory) 615 0$aCopulas (Mathematical statistics) 615 0$aDependence (Statistics) 615 0$aDistribution (Probability theory) 676 $a519.5 701 $aKurowicka$b Dorota$0474601 701 $aJoe$b Harry$0411519 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910788555203321 996 $aDependence modeling$93676432 997 $aUNINA