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A study on parsimonious periodic autoregressive model

모수 절약 주기적 자기회귀 모형에 관한 연구

  • Received : 2015.12.15
  • Accepted : 2016.01.02
  • Published : 2016.02.29

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.

Keywords

seasonal time series model;parsimony of principle;seasonality;ARIMA model;Holt-Winters model;unemployment rate

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