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Outliers in functional autoregressive time series

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  • Battaglia, Francesco
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    Abstract

    A method for identifying and estimating outliers in a time series is proposed, based on fitting functional autoregressive models. Both additive and innovation outliers may be defined. A simulation experiment and the analysis of some real data sets suggest that the proposed method is effective both for series following some nonlinear models, such as self-exciting threshold autoregressive or exponential autoregressive, and for linear series generated by autoregressive moving average processes.

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    File URL: http://www.sciencedirect.com/science/article/B6V1D-4FN2K5K-1/2/4664acf63f08839b8a3891c82262b161
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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 72 (2005)
    Issue (Month): 4 (May)
    Pages: 323-332

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    Handle: RePEc:eee:stapro:v:72:y:2005:i:4:p:323-332

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    Related research

    Keywords: Additive and innovation outliers Local linear regression Nonlinear models Varying-coefficient models;

    References

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    1. Jianqing Fan & Qiwei Yao & Zongwu Cai, 2003. "Adaptive varying-coefficient linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 57-80.
    2. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for ARCH in the Presence of Additive Outliers," Econometric Institute Research Papers EI 9659-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
    4. Zongwu Cai & Jianqing Fan & Qiwei Yao, 2000. "Functional-coefficient regression models for nonlinear time series," LSE Research Online Documents on Economics 6314, London School of Economics and Political Science, LSE Library.
    5. Francesco Battaglia & Lia Orfei, 2005. "Outlier Detection And Estimation In NonLinear Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(1), pages 107-121, 01.
    6. Cai, Zongwu & Ould-Saïd, Elias, 2003. "Local M-estimator for nonparametric time series," Statistics & Probability Letters, Elsevier, vol. 65(4), pages 433-449, December.
    7. Chen, Cathy W. S., 1997. "Detection of additive outliers in bilinear time series," Computational Statistics & Data Analysis, Elsevier, vol. 24(3), pages 283-294, May.
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