在都柏林湾的度的矢量时间序列建模
Amin Shoari Nejad1, Gerard D McCarthy2, Brian Kelleher3
1Hamilton Institute, Insight Centre for Data Analytics, Maynooth University, Kildare, Ireland.
Journal of applied statistics
|October 23, 2024
概括
这项研究使用矢量自回归集成条件异性 (VARICH) 方法模拟了都柏林湾的度. 研究结果表明,风速对度的影响比疏或倾倒活动更大.
科学领域:
- 环境科学 环境科学
- 水质监测 水质监测
- 时间序列分析时间序列分析
背景情况:
- 度是水质的一个关键指标.
- 人类活动如疏和倾倒可以改变度.
- 了解这些影响对于环境管理至关重要.
研究的目的:
- 为模拟都柏林湾的空间和时间度变化.
- 调查疏和倾倒对度的影响.
- 为了控制和与风速的影响进行比较.
主要方法:
- 开发了一种矢量自回归集成条件异二次性 (VARICH) 模型.
- 利用了2017-2018年每日度数据.
- 应用贝叶斯可信区间来量化不确定性.
主要成果:
- VARICH模型准确地反映了观察到的度数据.
- 模型的不确定性得到了良好的校准.
- 与风速相比,疏和倾倒对度的日常影响是可以忽略不计的.
结论:
- 风速是影响都柏林湾度的主要因素.
- VARICH模型为分析动态水质参数提供了一个强大的框架.
- 研究的人类活动对相对于大气条件的度的影响最小.
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