Asymptotic Statistical Analysis of Time Series: Clustering, Change Point, and Other Problems

author: Daniil Ryabko, SequeL lab, INRIA Lille - Nord Europe
published: May 28, 2013,   recorded: September 2012,   views: 2767
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Description

A method for constructing asymptotically consistent efficient algorithms for various statistical problems concerning stationary ergodic time series is presented. The considered problems include clustering, hypothesis testing, change-point estimation and others. The presented approach is based on empirical estimates ofthe distributional distance. Some open problems are also discussed.

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