Parsimonious test of dynamic interaction.
Parsimonious test of dynamic interaction.
复制标题
动态交互的简约测试。
DOI：
10.1002/ece3.4805
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发表时间：
2019
影响因子：
2.6
通讯作者：
Chisholm S
中科院分区：
文献类型：
--
作者：
Chisholm S
近年来，用于收集人类和动物运动和活动模式数据的技术取得了重大进展。作为定位数据的主要来源，GPS单元已经变得更便宜、更精确、更轻便、耗电量更少，并且随着惯性测量单元的加入，其精度得到了进一步提高。其结果是大量的地理空间时间序列数据，记录的速度从每几个小时一次定位（以最大限度地延长系统寿命）到每秒十次定位（在高动态情况下）。由于这种质量和数量的数据最近才出现，从原始位置数据中提取行为信息的分析方法处于早期发展阶段。这方面的一个例子是对动物运动模式的分析。在研究独居动物时，回避和联想的时间和地点是重要的行为标记。在本文中，提出了一种新的分析方法来检测个人之间的回避和关联;与现有的方法不同，不需要假设的领土的形状或个人运动的性质。模拟表明，假阳性（I型错误）是罕见的（1%-3%），这意味着测试很少表明存在关联，如果没有。
In recent years, there have been significant advances in the technology used to collect data on the movement and activity patterns of humans and animals. GPS units, which form the primary source of location data, have become cheaper, more accurate, lighter and less power‐hungry, and their accuracy has been further improved with the addition of inertial measurement units. The consequence is a glut of geospatial time series data, recorded at rates that range from one position fix every several hours (to maximize system lifetime) to ten fixes per second (in high dynamic situations). Since data of this quality and volume have only recently become available, the analytical methods to extract behavioral information from raw position data are at an early stage of development. An instance of this lies in the analysis of animal movement patterns. When investigating solitary animals, the timing and location of instances of avoidance and association are important behavioral markers. In this paper, a novel analytical method to detect avoidance and association between individuals is proposed; unlike existing methods, assumptions about the shape of the territories or the nature of individual movement are not needed. Simulations demonstrate that false positives (type I error) are rare (1%–3%), which means that the test rarely suggests that there is an association if there is none.