JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 644
Type: Contributed
Date/Time: Thursday, August 8, 2013 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #309783
Title: Breakpoint Detection of Nonstationary Time Series Using Wild Binary Segmentation
Author(s): Karolos Korkas*+ and Piotr Fryzlewicz
Companies: and London School of Economics
Keywords: Binary Segmentation ; Random Design ; Piecewise Stationarity ; Wavelet Periodogram ; Locally Stationary Wavelets ; Post-processing

We propose a new technique for consistent estimation of the breakpoints of a linear time series where the number and locations are unknown using the Wild Binary Segmentation (WBS) of Fryzlewicz (2012). We adopt the nonparametric Locally Stationary Wavelet model which provides a description of the second-order structure of a piecewise-stationary process through wavelet periodograms estimated at multiple scales and locations. The advantage of WBS is its localisation feature which means that it works in cases where the spacings between breakpoints are very short. In addition, we improve the performance of the algorithm by combining the breakpoints estimated from different scales and by using a post-processing step to eliminate spurious breakpoints. We finally provide an extensive simulation study to exhibit the good performance of the method.

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

Back to the full JSM 2013 program

2013 JSM Online Program Home

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

If you have questions about the Continuing Education 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.