Date of Award
May 2019
Degree Type
Thesis
Degree Name
Master of Science
Department
Mathematics
First Advisor
Daniel Gervini
Committee Members
David Spade, Chao Zhu
Abstract
This thesis proposes an outlier-resistant multiplicative component model for doubly stochastic point processes. The model is based on a principal component decomposition of the log-intensity functions, using heavy-tailed t-distributions for the component scores. As an example of application, the temporal distribution of bike check-out times in the Divvy bike sharing system of Chicago is analyzed using the t-model.
Recommended Citation
Elsaesser, Leo Stephan, "Outlier-Resistant Models for Doubly Stochastic Point Processes" (2019). Theses and Dissertations. 2064.
https://dc.uwm.edu/etd/2064