Assessing Heterogeneity in Transition Propensity in Multistate Capture-Recapture Data
Assessing Heterogeneity in Transition Propensity in Multistate Capture-Recapture Data
复制标题
评估多状态捕获-重捕获数据中转换倾向的异质性
DOI：
10.1111/rssc.12392
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Jeyam A
中科院分区：
文献类型：
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作者：
Jeyam A
多状态捕获-再捕获模型是帮助理解离散捕获-再捕获数据中的运动动力学的有用工具。然而，标准的多状态捕获-再捕获模型依赖于种群内生存、捕获和转移概率的同质性假设。有很多方法可以推广这个模型，所以非常需要一些关于真正需要什么的指导。在本文中，我们得到了一个新的测试，可以检测异质性的过渡倾向，并显示其良好的功能，通过使用模拟和应用程序的加拿大鹅数据集。我们还表明，传统上被用来诊断记忆的现有测试实际上是敏感的其他形式的过渡异质性，我们提出了修改后的测试，可以区分记忆和其他形式的过渡异质性。
Multistate capture–recapture models are a useful tool to help to understand the dynamics of movement within discrete capture–recapture data. The standard multistate capture–recapture model, however, relies on assumptions of homogeneity within the population with respect to survival, capture and transition probabilities. There are many ways in which this model can be generalized so some guidance on what is really needed is highly desirable. Within the paper we derive a new test that can detect heterogeneity in transition propensity and show its good power by using simulation and application to a Canada goose data set. We also demonstrate that existing tests which have traditionally been used to diagnose memory are in fact sensitive to other forms of transition heterogeneity and we propose modified tests which can distinguish between memory and other forms of transition heterogeneity.