MS (Master of Science)
Date of Award
Committee Chair or Co-Chairs
Michele Joyner, Yali Liu
This work discusses alternative methods to detect outliers in spatial point patterns.
Outliers are defined based on location only and also with respect to associated variables. Throughout the thesis we discuss five case studies, three of them come from experiments with spiders and bees, and the other two are data from earthquakes in a certain region. One of the main conclusions is that when detecting outliers from the point of view of location we need to take into consideration both the degree of clustering of the events and the context of the study. When detecting outliers from the point of view of an associated variable, outliers can be identified from a global or local perspective. For global outliers, one of the main questions addressed is whether the outliers tend to be clustered or randomly distributed in the region. All the work was done using the R programming language.
Thesis - Open Access
Liu, Jie, "Exploring Ways of Identifying Outliers in Spatial Point Patterns" (2015). Electronic Theses and Dissertations. Paper 2528. https://dc.etsu.edu/etd/2528
Copyright by the authors.