Detecting clusters with increased mean using scan windows with variable radius

Abstract

Applying spatiotemporal scan statistics is an effective method to detect the clustering of mean shifts in many application fields. Although several exponentially weighted moving average (EWMA) based scan statistics have been proposed, the existing methods generally require a fixed scan window size or apply the weighting technique across the temporal axis only. However, the size of shift coverage is often unavailable in practical problems. Using a mismatching scan radius may mislead the size of cluster coverage in space or delay the time to detection. This research proposed an stEWMA method by applying the weighting technique across both temporal and spatial axes with variable scan radius. The simulation analysis showed that the stEWMA method can have a significantly shorter time to detection than the likelihood ratio-based scan statistic using variable scan radius, especially when cluster coverage size is small. The application to detecting the increase of male thyroid cancer in the New Mexico state also showed the effectiveness of the proposed method.

Keywords:

• clustering
• mean shifts
• scan statistic
• spatiotemporal surveillance
• weight

Acknowledgements

We are grateful to the anonymous referees for their insightful suggestions that significantly improved the quality of this article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the National Science Council of Taiwan under Grant NSC [102-2221-E-155-071-MY2].