在空间过程模型下变化的方向速率
Banerjee Sudipto1, Alan E Gelfand2, C F Sirmans3
1Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455.
Journal of the American Statistical Association
|September 18, 2025
概括
本研究介绍了使用定向有限差异和衍生过程分析空间表面变化的方法. 这些技术在房地产和模拟数据分析的贝叶斯框架内应用.
科学领域:
- 空间统计的空间统计.
- 地质统计学 在地质统计学
- 环境建模环境建模
背景情况:
- 空间过程模型对于各种领域的数据推断至关重要.
- 兴趣往往在于量化空间表面的变化速率 (梯度).
- 例如包括环境梯度和数字高度模型评估.
研究的目的:
- 为了正式定制空间表面的定向有限差异和导数过程.
- 根据高斯假设,为这些过程开发一个完整的分布理论.
- 介绍一个贝叶斯推理框架来分析空间变化速率.
主要方法:
- 建立在平均平方可微分性概念的基础上.
- 假设数据或空间随机效应的静止高斯过程模型.
- 采用贝叶斯的推理框架.
主要成果:
- 获得完整的分布理论结果.
- 贝叶斯的方法为这种类型的空间分析提供了优势.
- 在模拟和房地产数据集上展示的方法.
结论:
- 提出的方法为分析空间表面的方向变化提供了一个强大的框架.
- 贝叶斯推理对于空间过程建模是有效的.
- 该方法适用于各种现实数据集,包括房地产价格.
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