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pro vyhledávání: '"Bean, Nigel G"'
We construct a stochastic fluid process with an underlying piecewise deterministic Markov process (PDMP) akin to the one used in the construction of the rational arrival process (RAP), which we call the RAP-modulated fluid process. As opposed to the
Externí odkaz:
http://arxiv.org/abs/2101.03242
Stochastic fluid-fluid models (SFFMs) offer powerful modeling ability for a wide range of real-life systems of significance. The existing theoretical framework for this class of models is in terms of operator-analytic methods. For the first time, we
Externí odkaz:
http://arxiv.org/abs/2010.13077
Publikováno v:
Adv. Appl. Probab. 53 (2021) 649-686
In this paper we provide the analysis of the limiting conditional distribution (Yaglom limit) for stochastic fluid models (SFMs), a key class of models in the theory of matrix-analytic methods. So far, transient and stationary analyses of the SFMs ha
Externí odkaz:
http://arxiv.org/abs/1908.10827
Akademický článek
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Tweet clustering for event detection is a powerful modern method to automate the real-time detection of events. In this work we present a new tweet clustering approach, using a probabilistic approach to incorporate temporal information. By analysing
Externí odkaz:
http://arxiv.org/abs/1811.05063
Publikováno v:
In Stochastic Processes and their Applications July 2022 149:308-340
Bayesian optimal experimental design has immense potential to inform the collection of data so as to subsequently enhance our understanding of a variety of processes. However, a major impediment is the difficulty in evaluating optimal designs for pro
Externí odkaz:
http://arxiv.org/abs/1703.05511
Modern social media platforms facilitate the rapid spread of information online. Modelling phenomena such as social contagion and information diffusion are contingent upon a detailed understanding of the information-sharing processes. In Twitter, an
Externí odkaz:
http://arxiv.org/abs/1703.05545
Autor:
Crotty, Stephen M., Minh, Bui Quang, Bean, Nigel G., Holland, Barbara R., Tuke, Jonathan, Jermiin, Lars S., von Haeseler, Arndt
Publikováno v:
Systematic Biology, 2020 Mar 01. 69(2), 249-264.
Externí odkaz:
https://www.jstor.org/stable/26939567
Publikováno v:
Stochastic Models. 2022, Vol. 38 Issue 3, p416-461. 46p.