Structured dependence between stochastic processes:
The relatively young theory of structured dependence between stochastic processes has many real-life applications in areas including finance, insurance, seismology, neuroscience, and genetics. With this monograph, the first to be devoted to the modeling of structured dependence between random proces...
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| Main Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2020
|
| Series: | Encyclopedia of mathematics and its applications
175 |
| Subjects: | |
| Online Access: | BSB01 EUV01 FHN01 UBA01 Volltext |
| Summary: | The relatively young theory of structured dependence between stochastic processes has many real-life applications in areas including finance, insurance, seismology, neuroscience, and genetics. With this monograph, the first to be devoted to the modeling of structured dependence between random processes, the authors not only meet the demand for a solid theoretical account but also develop a stochastic processes counterpart of the classical copula theory that exists for finite-dimensional random variables. Presenting both the technical aspects and the applications of the theory, this is a valuable reference for researchers and practitioners in the field, as well as for graduate students in pure and applied mathematics programs. Numerous theoretical examples are included, alongside examples of both current and potential applications, aimed at helping those who need to model structured dependence between dynamic random phenomena |
| Item Description: | Strong Markov consistency of multivariate Markov families and processes -- Consistency of finite multivariate Markov chains -- Consistency of finite multivariate conditional Markov chains -- Consistency of multivariate special semimartingales -- Strong Markov family structures -- Markov chain structures -- Conditional Markov chain structures -- Special semimartingale structures -- Archimedean survival processes, Markov consistency, ASP structures -- Generalized multivariate Hawkes processes -- Applications of stochastic structures |
| Physical Description: | 1 Online-Ressource (viii, 269 Seiten) |
| ISBN: | 9781316650530 |
| DOI: | 10.1017/9781316650530 |
Staff View
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| 520 | |a The relatively young theory of structured dependence between stochastic processes has many real-life applications in areas including finance, insurance, seismology, neuroscience, and genetics. With this monograph, the first to be devoted to the modeling of structured dependence between random processes, the authors not only meet the demand for a solid theoretical account but also develop a stochastic processes counterpart of the classical copula theory that exists for finite-dimensional random variables. Presenting both the technical aspects and the applications of the theory, this is a valuable reference for researchers and practitioners in the field, as well as for graduate students in pure and applied mathematics programs. Numerous theoretical examples are included, alongside examples of both current and potential applications, aimed at helping those who need to model structured dependence between dynamic random phenomena | ||
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| isbn | 9781316650530 |
| language | English |
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| spelling | Bielecki, Tomasz R. 1955- Verfasser (DE-588)12323400X aut Structured dependence between stochastic processes Tomasz R. Bielecki, Jacek Jakubowski, Mariusz Niewęgłowski Cambridge Cambridge University Press 2020 1 Online-Ressource (viii, 269 Seiten) txt rdacontent c rdamedia cr rdacarrier Encyclopedia of mathematics and its applications 175 175 Strong Markov consistency of multivariate Markov families and processes -- Consistency of finite multivariate Markov chains -- Consistency of finite multivariate conditional Markov chains -- Consistency of multivariate special semimartingales -- Strong Markov family structures -- Markov chain structures -- Conditional Markov chain structures -- Special semimartingale structures -- Archimedean survival processes, Markov consistency, ASP structures -- Generalized multivariate Hawkes processes -- Applications of stochastic structures The relatively young theory of structured dependence between stochastic processes has many real-life applications in areas including finance, insurance, seismology, neuroscience, and genetics. With this monograph, the first to be devoted to the modeling of structured dependence between random processes, the authors not only meet the demand for a solid theoretical account but also develop a stochastic processes counterpart of the classical copula theory that exists for finite-dimensional random variables. Presenting both the technical aspects and the applications of the theory, this is a valuable reference for researchers and practitioners in the field, as well as for graduate students in pure and applied mathematics programs. Numerous theoretical examples are included, alongside examples of both current and potential applications, aimed at helping those who need to model structured dependence between dynamic random phenomena Markov processes Dependence (Statistics) Jakubowski, Jacek 1954- Verfasser (DE-588)1217445668 aut Niewęgłowski, Mariusz 1976- Verfasser (DE-588)1217445846 aut Erscheint auch als Druck-Ausgabe 978-1-107-15425-4 Encyclopedia of mathematics and its applications 175 (DE-604)BV044777929 175 https://doi.org/10.1017/9781316650530 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Bielecki, Tomasz R. 1955- Jakubowski, Jacek 1954- Niewęgłowski, Mariusz 1976- Structured dependence between stochastic processes Encyclopedia of mathematics and its applications Markov processes Dependence (Statistics) |
| title | Structured dependence between stochastic processes |
| title_auth | Structured dependence between stochastic processes |
| title_exact_search | Structured dependence between stochastic processes |
| title_exact_search_txtP | Structured dependence between stochastic processes |
| title_full | Structured dependence between stochastic processes Tomasz R. Bielecki, Jacek Jakubowski, Mariusz Niewęgłowski |
| title_fullStr | Structured dependence between stochastic processes Tomasz R. Bielecki, Jacek Jakubowski, Mariusz Niewęgłowski |
| title_full_unstemmed | Structured dependence between stochastic processes Tomasz R. Bielecki, Jacek Jakubowski, Mariusz Niewęgłowski |
| title_short | Structured dependence between stochastic processes |
| title_sort | structured dependence between stochastic processes |
| topic | Markov processes Dependence (Statistics) |
| topic_facet | Markov processes Dependence (Statistics) |
| url | https://doi.org/10.1017/9781316650530 |
| volume_link | (DE-604)BV044777929 |
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