01003nam0 22002651i 450 SUN002656120061013120000.088-13-19110-320041026d1994 |0itac50 baitaIT|||| |||||ˆIl ‰servizio di tesoreria comunalemanuale di tecnica operativaGiuseppe Campo3. edPadovaCEDAM1994VIII, 598 p.24 cm.PadovaSUNL000007Campo, GiuseppeSUNV022162252550CEDAMSUNV005537650ITSOL20181109RICASUN0026561BIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE01 PREST IVB11 01 27752 BIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALEIT-CE010727752PREST IVB11paServizio di tesoreria comunale625986UNICAMPANIA03500nam 22005655 450 991086109370332120250807153135.03-031-57412-510.1007/978-3-031-57412-2(MiAaPQ)EBC31345498(Au-PeEL)EBL31345498(CKB)32074564800041(DE-He213)978-3-031-57412-2(EXLCZ)993207456480004120240517d2024 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierExtreme Values In Random Sequences /by Pavle Mladenović1st ed. 2024.Cham :Springer Nature Switzerland :Imprint: Springer,2024.1 online resource (287 pages)Springer Series in Operations Research and Financial Engineering,2197-17733-031-57411-7 Preface -- Regularly Varying Functions -- Basic Results of Extreme Value Theory -- Time Series and Missing Observations -- Combinatorial Problems and Extreme Values -- Bibliography -- Index.The 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.Springer Series in Operations Research and Financial Engineering,2197-1773ProbabilitiesStochastic processesStochastic analysisApplied ProbabilityStochastic ProcessesStochastic AnalysisProbabilities.Stochastic processes.Stochastic analysis.Applied Probability.Stochastic Processes.Stochastic Analysis.519Mladenović Pavle0MiAaPQMiAaPQMiAaPQBOOK9910861093703321Extreme Values in Random Sequences4163433UNINA