英文标题：
《Bessel-like birth-death process》
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作者：
Vygintas Gontis, Aleksejus Kononovicius
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最新提交年份：
2019
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英文摘要：
We consider models of the population or opinion dynamics which result in the non-linear stochastic differential equations (SDEs) exhibiting the spurious long-range memory. In this context, the correspondence between the description of the birth-death processes as the continuous-time Markov chains and the continuous SDEs is of high importance for the alternatives of modeling. We propose and generalize the Bessel-like birth-death process having clear representation by the SDEs. The new process helps to integrate the alternatives of description and to derive the equations for the probability density function (PDF) of the burst and inter-burst duration of the proposed continuous time birth-death processes.
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中文摘要：
我们考虑了导致非线性随机微分方程（SDE）表现出虚假长程记忆的人口或观点动态模型。在这种情况下，将生灭过程描述为连续时间马尔可夫链和连续SDE之间的对应关系对于建模的备选方案非常重要。我们提出并推广了类贝塞尔生灭过程，该过程具有明确的SDEs表示。新过程有助于整合描述的备选方案，并推导出所提出的连续时间出生-死亡过程的爆发和爆发间持续时间的概率密度函数（PDF）方程。
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分类信息：

一级分类：Physics 物理学
二级分类：Physics and Society 物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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