摘要翻译：
本文综述了近年来在工程、可靠性、公共卫生、生物医学和其他领域中出现的经常性事件的建模和分析方面的工作。递归事件建模具有独特的方面，使得它不同于单个事件设置，并且更难处理。例如，需要考虑事件发生次数不断增加的影响，应考虑协变量的影响，不能忽视单元内事件交互时间之间的潜在联系，需要考虑每次事件发生后进行干预的影响。本文描述了一种新的用于重复事件的通用模型，它同时适应了这些方面。给出了这类模型的统计推断方法，并通过实际数据集的应用说明了这类模型的统计推断方法。描述了一些现存的开放性研究问题。
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英文标题：
《Dynamic Modeling and Statistical Analysis of Event Times》
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作者：
Edsel A. Pe\~na
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最新提交年份：
2007
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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英文摘要：
  This review article provides an overview of recent work in the modeling and analysis of recurrent events arising in engineering, reliability, public health, biomedicine and other areas. Recurrent event modeling possesses unique facets making it different and more difficult to handle than single event settings. For instance, the impact of an increasing number of event occurrences needs to be taken into account, the effects of covariates should be considered, potential association among the interevent times within a unit cannot be ignored, and the effects of performed interventions after each event occurrence need to be factored in. A recent general class of models for recurrent events which simultaneously accommodates these aspects is described. Statistical inference methods for this class of models are presented and illustrated through applications to real data sets. Some existing open research problems are described.
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PDF链接：
https://arxiv.org/pdf/708.0343