The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A study on parsimonious periodic autoregressive model

모수 절약 주기적 자기회귀 모형에 관한 연구

  • Lee, Jiho (Department of Applied Statistics, Chung-Ang University) ;
  • Seong, Byeongchan (Department of Applied Statistics, Chung-Ang University)
  • 이지호 (중앙대학교 응용통계학과) ;
  • 성병찬 (중앙대학교 응용통계학과)
  • Received : 2015.12.15
  • Accepted : 2016.01.02
  • Published : 2016.02.29
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Abstract

This paper proposes a parsimonious periodic autoregressive (PAR) model. The proposed model performance is evaluated through an analysis of Korean unemployment rate series that is compared with existing models. We exploit some common features among each seasonality and confirm it by LR test for the parsimonious PAR model in order to impose a parsimonious structure on the PAR model. We observe that the PAR model tends to be superior to existing seasonal time series models in mid- and long-term forecasts. The proposed parsimonious model significantly improves forecasting performance.

본 논문에서는 주기적 자기회귀(periodic autoregressive) 모형에서 모수의 수를 줄이기 위한 모수 절약 주기적 자기회귀 모형을 연구하였다. 제안된 모수 절약 모형은 실증분석에서 실업률을 이용하여 기존의 계절 시계열 모형과 비교를 통하여 그 성능을 평가하였다. 모수 절약 구조를 부여하기 위하여 계절성에서 공통된 패턴을 찾아내는 방법을 사용하였으며 기존 주기적 자기회귀 모형과의 통계적 차이 유무는 LR 검정을 통해 확인하였다. 그 결과, 중장기적으로 주기적 자기회귀 모형이 기존의 계절시계열 모형보다 우수한 예측성능을 보였으며, 특히 모수 절약 주기적 자기 회귀 모형의 사용은 기존의 주기적 자기회귀 모형보다 우수한 예측성능을 나타내는 것을 확인하였다.

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References

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