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Truncating estimation for the change in stochastic trend with heavy-tailed innovations

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Abstract

A CUSUM estimator is proposed for the change point in stochastic trend with heavy-tailed innovations. In order to avoid the outliers caused by heavy-tailed innovations, we also construct a truncating CUSUM estimator. Results in this paper show that the CUSUM estimators are consistent. Simulations demonstrate that the truncating estimator behaves better for the heavy-tailed innovations.

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Authors and Affiliations

  1. Department of Applied Mathematics, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, People’s Republic of China

    Ruibing Qin, Zheng Tian & Hao Jin

  2. State Key Laboratory of Remote Sensing Science, 100101, Beijing, People’s Republic of China

    Zheng Tian

Authors
  1. Ruibing Qin
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  2. Zheng Tian
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  3. Hao Jin
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Correspondence to Ruibing Qin or Zheng Tian.

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Qin, R., Tian, Z. & Jin, H. Truncating estimation for the change in stochastic trend with heavy-tailed innovations. Stat Papers 52, 203–217 (2011). https://doi.org/10.1007/s00362-009-0223-y

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  • DOI: https://doi.org/10.1007/s00362-009-0223-y

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