| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 416058 | Computational Statistics & Data Analysis | 2009 | 8 Pages |
Abstract
A new method is proposed for identifying clusters in spatial point processes. It relies on a specific ordering of events and the definition of area spacings which have the same distribution as one-dimensional spacings. Then the spatial clusters are detected using a scan statistic adapted to the analysis of one-dimensional point processes. This flexible spatial scan test seems to be very powerful against any arbitrarily-shaped cluster alternative. These results have applications in epidemiological studies of rare diseases.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Lionel Cucala,