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Activity Number: 367
Type: Contributed
Date/Time: Wednesday, August 6, 2008 : 8:30 AM to 10:20 AM
Sponsor: Business and Economics Statistics Section
Abstract - #301566
Title: Estimation of Structural Breaks in Nonstationary Time Series: The Theory Behind AutoPARM
Author(s): Stacey Hancock*+ and Richard A. Davis and Yi-Ching Yao
Companies: Colorado State University and Columbia University and Institute of Statistical Science, Academia Sinica
Address: 1850 Laporte Ave Apt D22, Fort Collins, CO, 80521,
Keywords: time series ; changepoint analysis
Abstract:

Many time series exhibit structural breaks, jumping to different stationary processes at times called "changepoints." The goal of this research is to estimate where these structural breaks occur and to provide a model for the data within each stationary segment. The program AutoPARM (Automatic Piecewise AutoRegressive Modeling), developed by Davis, Lee, and Rodriguez-Yam (2006), uses the minimum description length principle to estimate the number and locations of changepoints in a time series by fitting autoregressive models to each segment. This research shows that when the true underlying model is segmented autoregressive, the estimates obtained by AutoPARM are consistent. Under a more general time series model exhibiting structural breaks, AutoPARM's estimates demonstrate consistency-like properties.

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