A1214
Title: On regime changes in text data using hidden Markov model of contaminated von Mises-Fisher distribution
Authors: Yingying Zhang - Western Michigan Univesity (United States)
Shuchismita Sarkar - Bowling Green State University (United States) [presenting]
Yuanyuan Chen - University of Alabama (United States)
Xuwen Zhu - University of Alabama (United States)
Abstract: The purpose is to present a novel methodology for analyzing temporal directional data with scatter and heavy tails. A hidden Markov model with contaminated von Mises-Fisher emission distribution is developed. The model is implemented using a forward and backward selection approach that provides additional flexibility for contaminated as well as non-contaminated data. The utility of the method for finding homogeneous time blocks (regimes) is demonstrated in several experimental settings and two real-life text data sets containing presidential addresses and corporate financial statements, respectively.
