A Nonparametric Index for Determining the Numbers of Events in Clusters
文献类型：SCI/SSCI论文
| 作者 | Pei T. |
| 发表日期 | 2011 |
| 关键词 | Nearest-neighbor Feature Noise Cluster Poisson process Complete spatial randomness spatial-patterns plant-populations point-processes distance randomness estimators angles |
| 英文摘要 | The task of discriminating between heterogeneity and complete spatial randomness (CSR) for a given point process can be divided into three subtasks: the identification of the point pattern; the determination of the sizes of clusters; and the estimation of the numbers of events in dominant clusters. Many studies have been performed regarding the first and second subtasks. However, limited work has been done on the third aspect; hence, the determination of the number of events in each dominant cluster is still an unsolved problem. In this paper, we provide a solution by constructing a new index which is defined as the ratio between the variance of the (k+1)th nearest distance and that of the kth nearest distance. Our method can be divided into two phases: the detection of point pattern and the estimation of the numbers of events in dominant clusters. These phases can be estimated by the values at which the index abruptly decreases to be less than 1. A comparative study between the existing indices and our index shows the following: (i) our index can indicate the numbers of events in dominant clusters in a relatively objective way, which is different from the K-function revealing the sizes of clustered patterns; (ii) it is a nonparametric index and is easy to implement; and (iii) it demonstrates the highest detection power for differentiating between heterogeneity and CSR. The simulations and two seismic case studies also confirmed the correctness of our method. |
| 出处 | Mathematical Geosciences |
| 卷 | 43 |
| 期 | 3 |
| 页 | 345-362 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1874-8961 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/23224]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Pei T.. A Nonparametric Index for Determining the Numbers of Events in Clusters. 2011. |
入库方式： OAI收割
来源：地理科学与资源研究所
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