Degree Type
Creative Component
Semester of Graduation
Fall 2018
Department
Statistics
First Major Professor
Zhengyuan Zhu
Degree(s)
Master of Science (MS)
Major(s)
Statistics
Abstract
Detecting weak clustered signal in spatial data is important but challenging in applications such as medical image and epidemiology. A more efficient detection algorithm can provide more precise early warning, and effectively reduce the decision risk and cost. To date, many methods have been developed to detect signals with spatial structures. However, most of the existing methods are either too conservative for weak signals or computationally too intensive. In this paper, we consider a novel method named Spatial CUSUM (SCUSUM), which employs the idea of the CUSUM procedure and false discovery rate controlling. We develop theoretical properties of the method which indicates that asymptotically SCUSUM can reach high classification accuracy. In the simulation study, we demonstrate that SCUSUM is sensitive to weak spatial signals. This new method is applied to a real fMRI dataset as illustration, and more irregular weak spatial signals are detected in the images compared to some existing methods, including the conventional FDR, FDR$_L$ and scan statistics.
Copyright Owner
The Authors
Copyright Year
2018
File Format
application/pdf
Recommended Citation
Zhang, Xin and Zhu, Zhengyuan, "Spatial CUSUM for Signal Region Detection" (2018). Creative Components. 120.
https://lib.dr.iastate.edu/creativecomponents/120
