二元间歇泉喷发系统的协变量调整递归事件过程建模
Modeling Bivariate Geyser Eruption System with Covariate-Adjusted Recurrent Event Process
摘要：
间歇泉喷发是黄石国家公园最受欢迎的标志性景点之一。间歇泉喷发的相互依赖性和协变量的影响是间歇泉研究中的研究人员感兴趣的。在本文中，我们提出了一个参数协变量调整的复发事件模型估计喷发间隙时间。描述了一个一般的二元递归事件过程，其中二元对数正态分布和具有不同边缘分布的Gumbel copula被用来建模一个相互依赖的二元事件系统.采用极大似然法估计模型参数。所提出的方法被应用到分析黄石国家公园的间歇泉喷发数据的二元间歇泉系统，并提供了更深入的了解事件发生机制的个别事件，以及作为一个整体的系统。一个全面的仿真研究进行评估所提出的方法的性能。
英文摘要：
Geyser eruption is one of the most popular signature attractions at the Yellowstone National Park. The interdependence of geyser eruptions and impacts of covariates are of interest to researchers in geyser studies. In this paper, we propose a parametric covariate-adjusted recurrent event model for estimating the eruption gap time. We describe a general bivariate recurrent event process, where a bivariate lognormal distribution and a Gumbel copula with different marginal distributions are used to model an interdependent dual-type event system. The maximum likelihood approach is used to estimate model parameters. The proposed method is applied to analyzing the Yellowstone geyser eruption data for a bivariate geyser system and offers a deeper understanding of the event occurrence mechanism of individual events as well as the system as a whole. A comprehensive simulation study is conducted to evaluate the performance of the proposed method.
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