{"title":"Multivariate Hawkes processes with simultaneous occurrence of excitation events coming from different sources","authors":"T. Bielecki, J. Jakubowski, Mariusz Niewęgłowski","doi":"10.1080/15326349.2022.2134896","DOIUrl":null,"url":null,"abstract":"Abstract This work contributes to the theory of Hawkes processes. We introduce and study a new class of Hawkes processes that we call generalized Hawkes processes, and their special subclass – the generalized multivariate Hawkes processes (GMHPs). GMHPs are multivariate marked point processes that add an important feature to the family of the (classical) multivariate Hawkes processes: they allow for explicit modeling of simultaneous occurrence of excitation events coming from different sources, i.e., caused by different coordinates of the multivariate process.","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":"39 1","pages":"537 - 565"},"PeriodicalIF":0.5000,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stochastic Models","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/15326349.2022.2134896","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract This work contributes to the theory of Hawkes processes. We introduce and study a new class of Hawkes processes that we call generalized Hawkes processes, and their special subclass – the generalized multivariate Hawkes processes (GMHPs). GMHPs are multivariate marked point processes that add an important feature to the family of the (classical) multivariate Hawkes processes: they allow for explicit modeling of simultaneous occurrence of excitation events coming from different sources, i.e., caused by different coordinates of the multivariate process.
期刊介绍:
Stochastic Models publishes papers discussing the theory and applications of probability as they arise in the modeling of phenomena in the natural sciences, social sciences and technology. It presents novel contributions to mathematical theory, using structural, analytical, algorithmic or experimental approaches. In an interdisciplinary context, it discusses practical applications of stochastic models to diverse areas such as biology, computer science, telecommunications modeling, inventories and dams, reliability, storage, queueing theory, mathematical finance and operations research.