Locating Changes in Highly Dependent Data with an Unknown Number of Change Points

author: Azadeh Khaleghi, SequeL lab, INRIA Lille - Nord Europe
published: Jan. 14, 2013,   recorded: December 2012,   views: 2862


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The problem of multiple change point estimation is considered for sequences with unknown number of change points. A consistency framework is suggested that is suitable for highly dependent time-series, and an asymptotically consistent algorithm is proposed. In order for the consistency to be established the only assumption required is that the data is generated by stationary ergodic time-series distributions. No modeling, independence or parametric assumptions are made; the data are allowed to be dependent and the dependence can be of arbitrary form. The theoretical results are complemented with experimental evaluations.

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