Spatial and Spatio-Temporal Scan Statistics of the Regression Coefficients

• Activity Number: 413 - Analyses of Environmental Data
• Type: Contributed
• Date/Time: Thursday, August 12, 2021 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Junho Lee* and Jun Zhu and Ronald Gangnon and Ying Sun
• Companies: Baylor University and University of Wisconsin-Madison and University of Wisconsin-Madison and King Abdullah University of Science and Technology (KAUST)
• Keywords: regression; regression coefficient; scan statistic; spatial cluster detection; spatio-temporal cluster detection

Abstract

Spatial or spatio-temporal cluster detection is an important problem in a variety of scientific disciplines such as environmental sciences, epidemiology, and sociology. Scan statistic and its variants have been popular approaches in the last three decades, and most of them are all defined in terms of the responses. However, in regression analysis for spatial or spatio-temporal data, identifying clusters of spatial units in a regression coefficient could provide insight into the unique relationship between a response and covariates in certain subdomains of space and time windows relative to the background in other parts of the domains. Several recent studies have addressed the cluster detection problem of regression coefficients for spatial or spatio-temporal data. We introduce these recent scan statistic approaches from identifying spatial or spatio-temporal clusters in regression models to addressing the potential spatial dependency.