Using the maximum clustering heterogeneous set-proportion to select the maximum window size for the spatial scan statistic.

ABSTRACT: The spatial scan statistic has been widely used to detect spatial clusters that are of common interest in many health-related problems. However, in most situations, different scan parameters, especially the maximum window size (MWS), result in obtaining different detected clusters. Although performance measures can select an optimal scan parameter, most of them depend on historical prior or true cluster information, which is usually unavailable in practical datasets. Currently, the Gini coefficient and the maximum clustering set-proportion statistic (MCS-P) are used to select appropriate parameters without any prior information. However, the Gini coefficient may be unstable and select inappropriate parameters, especially in complex practical datasets, while the MCS-P may have unsatisfactor

SUBMITTER: Wang W 

PROVIDER: S-EPMC7078301 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature