JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 575
Type: Contributed
Date/Time: Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #312814 View Presentation
Title: Time-Frequency Functional Models for Categorical Time Series
Author(s): Yuelei Sui*+ and Scott Holan and Christopher K. Wikle
Companies: and University of Missouri and University of Missouri
Keywords: Bayesian hierarchical models ; Spectral envelope ; Time-frequency

In an era of Big Data, time-varying spectral analysis has become an increasingly important tool for many scientific investigations. Making the transformation to the time-frequency domain provides a convenient and powerful data compression platform for extracting important features of many nonstationary time series. For categorical time series notions of time-frequency have received considerably less attention. In this direction, we propose a Bayesian framework that utilizes time-varying spectral envelopes as predictors in modeling complex processes. Importantly, our approach extracts features of the original signal that improve prediction rather than explaining variation. Finally, we illustrate the effectiveness of our approach through simulation and through a real-data application.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2014 program

2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.