Electronic Journal of Statistics

On distinguishing multiple changes in mean and long-range dependence using local Whittle estimation

Changryong Baek and Vladas Pipiras

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It is well known that changes in mean superimposed by a short-range dependent series can be confused easily with long-range dependence. A procedure to distinguish the two phenomena is introduced. The proposed procedure is based on the local Whittle estimation of the long-range dependence parameter applied to the series after removing changes in mean, and comparing the results to those obtained through the available CUSUM-like approaches. According to the proposed procedure, for example, volatility series in finance seem more consistent with the changes-in-mean models whereas hydrology and telecommunication series are more in line with long-range dependence. As part of this work, a new method based on the local Whittle estimation to find the number of breaks is also introduced and its consistency is proved for the changes-in-mean models.

Article information

Electron. J. Statist., Volume 8, Number 1 (2014), 931-964.

First available in Project Euclid: 29 July 2014

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84] 62G10: Hypothesis testing
Secondary: 60G18: Self-similar processes

Hypothesis tests size and power short- and long-range dependence changes in mean local Whittle estimator bootstrap


Baek, Changryong; Pipiras, Vladas. On distinguishing multiple changes in mean and long-range dependence using local Whittle estimation. Electron. J. Statist. 8 (2014), no. 1, 931--964. doi:10.1214/14-EJS916. https://projecteuclid.org/euclid.ejs/1406638930

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