LEADER 03500nam 22005655 450 001 9910861093703321 005 20250807153135.0 010 $a3-031-57412-5 024 7 $a10.1007/978-3-031-57412-2 035 $a(MiAaPQ)EBC31345498 035 $a(Au-PeEL)EBL31345498 035 $a(CKB)32074564800041 035 $a(DE-He213)978-3-031-57412-2 035 $a(EXLCZ)9932074564800041 100 $a20240517d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExtreme Values In Random Sequences /$fby Pavle Mladenovi? 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (287 pages) 225 1 $aSpringer Series in Operations Research and Financial Engineering,$x2197-1773 311 08$a3-031-57411-7 327 $aPreface -- Regularly Varying Functions -- Basic Results of Extreme Value Theory -- Time Series and Missing Observations -- Combinatorial Problems and Extreme Values -- Bibliography -- Index. 330 $aThe main subject is the probabilistic extreme value theory. The purpose is to present recent results related to limiting distributions of maxima in incomplete samples from stationary sequences, and results related to extremal properties of different combinatorial configurations. The necessary contents related to regularly varying functions and basic results of extreme value theory are included in the first two chapters with examples, exercises and supplements. The motivation for consideration maxima in incomplete samples arises from the fact that real data are often incomplete. A sequence of observed random variables from a stationary sequence is also stationary only in very special cases. Hence, the results provided in the third chapter are also related to non-stationary sequences. The proof of theorems related to joint limiting distribution of maxima in complete and incomplete samples requires a non-trivial combination of combinatorics and point process theory. Chapter four provides results on the asymptotic behavior of the extremal characteristics of random permutations, the coupon collector's problem, the polynomial scheme, random trees and random forests, random partitions of finite sets, and the geometric properties of samples of random vectors. The topics presented here provide insight into the natural connections between probability theory and algebra, combinatorics, graph theory and combinatorial geometry. The contents of the book may be useful for graduate students and researchers who are interested in probabilistic extreme value theory and its applications. 410 0$aSpringer Series in Operations Research and Financial Engineering,$x2197-1773 606 $aProbabilities 606 $aStochastic processes 606 $aStochastic analysis 606 $aApplied Probability 606 $aStochastic Processes 606 $aStochastic Analysis 615 0$aProbabilities. 615 0$aStochastic processes. 615 0$aStochastic analysis. 615 14$aApplied Probability. 615 24$aStochastic Processes. 615 24$aStochastic Analysis. 676 $a519 700 $aMladenovic?$b Pavle$00 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910861093703321 996 $aExtreme Values in Random Sequences$94163433 997 $aUNINA