Time Series Segmentation Procedures to Detect, Locate and Estimate Change-Points [chapter]

Ana Laura Badagián, Regina Kaiser, Daniel Peña
2014 Empirical Economic and Financial Research  
This article deals with the problem of detecting, locating, and estimating the change-points in a time series process. We are interested in finding changes in the mean and the autoregressive coefficients in piecewise autoregressive processes, as well as changes in the variance of the innovations. With this objective, we propose an approach based on the Bayesian information criterion (BIC) and binary segmentation. The proposed procedure is compared with several others available in the literature
more » ... which are based on cusum methods (Inclán and Tiao, J Am Stat Assoc 89 (427) :913-923, 1994), minimum description length principle (Davis et al., J Am Stat Assoc 101(473):229-239, 2006), and the time varying spectrum (Ombao et al., Ann Inst Stat Math 54 (1) : 2002). We computed the empirical size and power properties of the available procedures in several Monte Carlo scenarios and also compared their performance in a speech recognition dataset.
doi:10.1007/978-3-319-03122-4_3 fatcat:dqdppblbg5hlfdxx3fx66fsh54