001441483 000__ 03279cam\a2200553Ii\4500
001441483 001__ 1441483
001441483 003__ OCoLC
001441483 005__ 20230309004741.0
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001441483 019__ $$a1291147049$$a1291171923$$a1291318189$$a1292354006$$a1294361589
001441483 020__ $$a9783030846398$$q(electronic bk.)
001441483 020__ $$a3030846393$$q(electronic bk.)
001441483 020__ $$z9783030846381
001441483 020__ $$z3030846385
001441483 0247_ $$a10.1007/978-3-030-84639-8$$2doi
001441483 035__ $$aSP(OCoLC)1290840144
001441483 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCO$$dDCT$$dOCLCF$$dOCLCO$$dOCLCQ
001441483 049__ $$aISEA
001441483 050_4 $$aQA401$$b.L38 2021
001441483 08204 $$a511/.8$$223
001441483 1001_ $$aLaub, Patrick J.,$$eauthor.
001441483 24514 $$aThe elements of Hawkes processes /$$cPatrick J. Laub, Young Lee, Thomas Taimre.
001441483 264_1 $$aCham :$$bSpringer,$$c[2021]
001441483 264_4 $$c©2021
001441483 300__ $$a1 online resource :$$billustrations (chiefly color)
001441483 336__ $$atext$$btxt$$2rdacontent
001441483 337__ $$acomputer$$bc$$2rdamedia
001441483 338__ $$aonline resource$$bcr$$2rdacarrier
001441483 347__ $$atext file$$bPDF$$2rda
001441483 504__ $$aIncludes bibliographical references.
001441483 5050_ $$aBackground -- Hawes Process Essentials -- Simulation Methods -- Likelihood Methods -- EM Algorithm -- Bayesian Methods -- Spectral Methods -- Goodness of Fit -- Traditional Applications -- Financial and Actuarial Applications -- Biological Applications.
001441483 506__ $$aAccess limited to authorized users.
001441483 520__ $$aHawkes processes are studied and used in a wide range of disciplines: mathematics, social sciences, and earthquake modelling, to name a few. This book presents a selective coverage of the core and recent topics in the broad field of Hawkes processes. It consists of three parts. Parts I and II summarise and provide an overview of core theory (including key simulation methods) and inference methods, complemented by a selection of recent research developments and applications. Part III is devoted to case studies in seismology and finance that connect the core theory and inference methods to practical scenarios. This book is designed primarily for applied probabilists, statisticians, and machine learners. However, the mathematical prerequisites have been kept to a minimum so that the content will also be of interest to undergraduates in advanced mathematics and statistics, as well as machine learning practitioners. Knowledge of matrix theory with basics of probability theory, including Poisson processes, is considered a prerequisite. Colour-blind-friendly illustrations are included.
001441483 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 21, 2022).
001441483 650_0 $$aMathematical models.
001441483 650_0 $$aMathematical statistics.
001441483 650_6 $$aModèles mathématiques.
001441483 655_0 $$aElectronic books.
001441483 7001_ $$aLee, Young,$$eauthor.
001441483 7001_ $$aTaimre, Thomas,$$d1983-$$eauthor.
001441483 77608 $$iPrint version: $$z3030846385$$z9783030846381$$w(OCoLC)1260133389
001441483 852__ $$bebk
001441483 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-84639-8$$zOnline Access$$91397441.1
001441483 909CO $$ooai:library.usi.edu:1441483$$pGLOBAL_SET
001441483 980__ $$aBIB
001441483 980__ $$aEBOOK
001441483 982__ $$aEbook
001441483 983__ $$aOnline
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