Authors: | Rooch, Aeneas Zelo, Ieva Fried, Roland |
Title: | Estimation methods for the LRD parameter under a change in the mean |
Language (ISO): | en |
Abstract: | When analyzing time series which are supposed to exhibit long-range dependence (LRD), a basic issue is the estimation of the LRD parameter, for example the Hurst parameter H 2 (1=2; 1). Conventional estimators of H easily lead to spurious detection of long memory if the time series includes a shift in the mean. This defect has fatal consequences in change-point problems: Tests for a level shift rely on H, which needs to be estimated before, but this estimation is distorted by the level shift. We investigate two blocks approaches to adapt estimators of H to the case that the time series includes a jump and compare them with other natural techniques as well as with estimators based on the trimming idea via simulations. These techniques improve the estimation of H if there is indeed a change in the mean. In the absence of such a change, the methods little affect the usual estimation. As adaption, we recommend an overlapping blocks approach: If one uses a consistent estimator, the adaption will preserve this property and it performs well in simulations. |
Subject Headings: | Hurst parameter change-point problems long memory long-range dependence jump estimation |
URI: | http://hdl.handle.net/2003/35124 http://dx.doi.org/10.17877/DE290R-17171 |
Issue Date: | 2016 |
Appears in Collections: | Sonderforschungsbereich (SFB) 823 |
Files in This Item:
File | Description | Size | Format | |
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DP_3216_SFB823_Rooch_Zelo_Fried.pdf | DNB | 455.32 kB | Adobe PDF | View/Open |
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