Communications for Statistical Applications and Methods

  • 제18권4호
  • /
  • Pages.517-525
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  • 2011
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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이상 트래픽 탐지를 위한 로버스트 추정 방법 비교 연구

A Comparative Study of a Robust Estimate Method for Abnormal Traffic Detection

  • Jung, Jae-Yoon (Department of Statistics, Chung-Ang University) ;
  • Kim, Sahm (Department of Statistics, Chung-Ang University)
  • 투고 : 20110200
  • 심사 : 20110300
  • 발행 : 2011.07.31
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초록

본 연구는 이상치가 존재하는 자료에 적용될 수 있는 방법을 비교한 연구로서, 이분산 시계열 모형 하에서 로버스트 추정 방법의 효용성을 보이고자 한다. GARCH 모형하에서 이상치 탐지 기법과 GARCH 모형을기반한 로버스트 추정방법의 성능을 비교하였다. 실제 인터넷 트래픽 자료에 두 방법을 적용했을때, 로버스트 추정방법이 이상치 탐지 기법에 비해 덜 복잡하고 성능이 우수함을 입증하였다.

This paper shows the performance evaluation of a robust estimator based on the GARCH model. We first introduce the method of a robust estimate in the GARCH model and the method of an outlier detection in the GARCH model. The results of the real internet traffic data show the out-performance of the robust estimator over the outlier detection method in the GARCH model. In addition, the method of the robust estimate is less complex than the method of the outlier detection method in the GARCH model.

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참고문헌

  1. 하명호, 김삼용(2010). 재무 시계열 자료의 이상치 탐지 기법 연구, <응용통계연구>, 23, 41-47. https://doi.org/10.5351/KJAS.2010.23.1.041
  2. Basawa, I. V., Huggins, R. M. and Staudte, R. G. (1985). Robust test for time series with an application to first-order autoregressive processes, Biometrika, 72, 559-571. https://doi.org/10.1093/biomet/72.3.559
  3. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31, 307-327. https://doi.org/10.1016/0304-4076(86)90063-1
  4. Box, G. E. P. and Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control, Holden Day, San Francisco.
  5. Charles, A. and Darne, O. (2005). Outliers and GARCH models in financial data, Journal of Economics Letters, 86, 347-352. https://doi.org/10.1016/j.econlet.2004.07.019
  6. Denby, L. and Martin, R. D. (1979). Robust estimation of the first order autoregressive parameter, Journal of the American Statistical Association, 74, 140-146. https://doi.org/10.2307/2286743
  7. Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation, Econometrica, 50, 987-1007. https://doi.org/10.2307/1912773
  8. Fox, A. J. (1972). Outliers in time series, Journal of Royal Statistical Society B, 34, 350-363.
  9. Franses, P. H. and Ghijsels, H. (1999). Additive outliers, GARCH and forecasting volatility, International Journal of Forecasting, 15, 1-9. https://doi.org/10.1016/S0169-2070(98)00053-3
  10. Huber, P. (1981). Robust Statistics, Wiley, New York.
  11. Martin, R. D. (1980). Robust Estimation of Autoregressive Models (with discussion). Directions in Time Series, The Institute of Mathematical Statistics Publishers, Hayward, 228-262.
  12. Martin, R. D. (1982). The Cramer-Rao bound and robust M-estimates for autoregressions, Biometrika, 69, 437-442.
  13. Martin, R. D. and Yohai, V. J. (1985). Robustness in Time Series and Estimating ARMA Models, Handbook of Statistics, 4, Elsevier, New York.
  14. Shao, Q. (2008). Robust estimation for periodic autoregressive time series, Journal of Time Series Analysis, 29, 251-263. https://doi.org/10.1111/j.1467-9892.2007.00555.x