图 书 馆
空间异常检测的广义局部统计方法GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection |
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| 课程网址: | http://videolectures.net/kdd2010_chen_glssod/ |
| 主讲教师: | Feng Chen |
| 开课单位: | 纽约州立大学 |
| 开课时间: | 2010-10-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Local based approach is a major category of methods for spatial outlier detection (SOD). Currently, there is a lack of systematic analysis on the statistical properties of this framework. For example, most methods assume identical and independent normal distributions (i.i.d. normal) for the calculated local differences, but no justifications for this critical assumption have been presented. The methods' detection performance on geostatistic data with linear or nonlinear trend is also not well studied. In addition, there is a lack of theoretical connections and empirical comparisons between local and global based SOD approaches. This paper discusses all these fundamental issues under the proposed Generalized Local Statistical (GLS) framework. Furthermore, robust estimation and outlier detection methods are designed for the new GLS model. Extensive simulations demonstrated that the SOD method based on the GLS model significantly outperformed all existing approaches when the spatial data exhibits a linear or nonlinear trend. |
| 关 键 词: | 空间异常; 主要方法; 统计特性 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-05-10：cwx |
| 阅读次数: | 96 |