LEADER 03689nam 22006135 450 001 996418273703316 005 20200701165057.0 010 $a1-0716-0737-5 024 7 $a10.1007/978-1-0716-0737-4 035 $a(CKB)4100000011325643 035 $a(DE-He213)978-1-0716-0737-4 035 $a(MiAaPQ)EBC6245900 035 $a(PPN)269145729 035 $a(EXLCZ)994100000011325643 100 $a20200701d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHeavy-Tailed Time Series$b[electronic resource] /$fby Rafal Kulik, Philippe Soulier 205 $a1st ed. 2020. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2020. 215 $a1 online resource (XIX, 681 p. 7 illus., 5 illus. in color.) 225 1 $aSpringer Series in Operations Research and Financial Engineering,$x1431-8598 311 $a1-0716-0735-9 320 $aIncludes bibliographical references and index. 327 $aRegular variation -- Regularly varying random variables -- Regularly varying random vectors -- Dealing with extremal independence -- Regular variation of series and random sums -- Regularly varying time series -- Limit theorems -- Convergence of clusters-. Point process convergence -- Convergence to stable and extremal processes -- The tall empirical and quantile processes -- Estimation of cluster functionals -- Estimation for extremally independent time series -- Bootstrap -- Time series models -- Max-stable processes -- Markov chains -- Moving averages -- Long memory processes -- Appendices. . 330 $aThis book aims to present a comprehensive, self-contained, and concise overview of extreme value theory for time series, incorporating the latest research trends alongside classical methodology. Appropriate for graduate coursework or professional reference, the book requires a background in extreme value theory for i.i.d. data and basics of time series. Following a brief review of foundational concepts, it progresses linearly through topics in limit theorems and time series models while including historical insights at each chapter?s conclusion. Additionally, the book incorporates complete proofs and exercises with solutions as well as substantive reference lists and appendices, featuring a novel commentary on the theory of vague convergence. 410 0$aSpringer Series in Operations Research and Financial Engineering,$x1431-8598 606 $aProbabilities 606 $aStatistics  606 $aApplied mathematics 606 $aEngineering mathematics 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aApplications of Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M13003 615 0$aProbabilities. 615 0$aStatistics . 615 0$aApplied mathematics. 615 0$aEngineering mathematics. 615 14$aProbability Theory and Stochastic Processes. 615 24$aStatistical Theory and Methods. 615 24$aApplications of Mathematics. 676 $a519.24 700 $aKulik$b Rafal$4aut$4http://id.loc.gov/vocabulary/relators/aut$01015107 702 $aSoulier$b Philippe$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996418273703316 996 $aHeavy-Tailed Time Series$92368777 997 $aUNISA