응용통계연구 (The Korean Journal of Applied Statistics)

  • 제21권6호
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  • Pages.1037-1044
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  • 2008
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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멱변환 이분산성 시계열 모형을 이용한 인터넷 트래픽 예측 기법 연구

Internet Traffic Forecasting Using Power Transformation Heteroscadastic Time Series Models

  • Ha, M.H. (Dept. of Statistics, Chung-Ang University) ;
  • Kim, S. (Dept. of Statistics, Chung-Ang University)
  • 발행 : 2008.12.31
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초록

본 연구에서는 재무시계얼 자료의 변동성을 분석하는데 유용하게 쓰이는 멱변환 시계열 모형을 인터넷 트래픽 자료 특성 분석에 적용하여 효용성을 보이고자 한다. 트래픽의 특성인 장기기억(long memory)특성을 설명하기 위하여 멱변환 GARCH(PGARCH) 모형을 소개하고 기존의 GARCH 모형보다 더 유용함을 시뮬레이션과 실제 인터넷 트래픽 자료에 적합시켜 입증하였다.

In this paper, we show the performance of the power transformation GARCH(PGARCH) model to analyze the internet traffic data. The long memory property which is the typical characteristic of internet traffic data can be explained by the PGARCH model rather than the linear GARCH model. Small simulation and the analysis of the real internet traffic show the out-performance of the PARCH MODEL over the linear GARCH one.

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참고문헌

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피인용 문헌

  1. A Study on Internet Traffic Forecasting by Combined Forecasts vol.28, pp.6, 2015, https://doi.org/10.5351/KJAS.2015.28.6.1235
  2. Re-Transformation of Power Transformation for ARMA(p, q) Model - Simulation Study vol.28, pp.3, 2015, https://doi.org/10.5351/KJAS.2015.28.3.511