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관광 수요를 위한 결합 예측 모형에 대한 연구

A Study on the Tourism Combining Demand Forecasting Models for the Tourism in Korea

  • 손흥구 (중앙대학교 응용통계학과) ;
  • 하명호 (중앙대학교 응용통계학과) ;
  • 김삼용 (중앙대학교 응용통계학과)
  • Son, H.G. (Department of Applied Statistics, Chung-Ang University) ;
  • Ha, M.H. (Department of Applied Statistics, Chung-Ang University) ;
  • Kim, S. (Department of Applied Statistics, Chung-Ang University)
  • 투고 : 2012.02.27
  • 심사 : 2012.03.28
  • 발행 : 2012.04.30

초록

본 논문은 일별 관광수요 자료를 분석하기 위하여 시계열의 대표적인 3개 모형인 ARIMA, Holt-Winters, AR-GARCH 모형을 적용하였다. 모형의 성능을 비교하기 위해 Armstrong (2001)이 제안한 방법을 이용하여 서로 다른 방법의 예측값을 단순결합과 MSE, SE를 이용한 결합법을 이용하여 정확도 높일 수 있음을 확인하였다.

This paper applies forecasting models such as ARIMA, Holt-Winters and AR-GARCH models to analyze daily tourism data in Korea. To evaluate the performance of the models, we need single and double seasonal models that compare the RMSE and SE for a better accuracy of the forecasting models based on Armstrong (2001).

키워드

참고문헌

  1. 윤지성, 허남균, 김삼용, 허희영 (2010). 계절형 다변량 시계열 모형을 이용한 국제항공 여객 및 화물 수요예측에 관한 연구, <한국통계학회 논문집>, 17, 473-481. https://doi.org/10.5351/CKSS.2010.17.3.473
  2. 허남균, 정재윤, 김삼용 (2009). 다변량 시계열 모형을 이용한 항공 수요 예측 연구, <응용통계연구>, 22, 1007-1077. https://doi.org/10.5351/KJAS.2009.22.5.1007
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피인용 문헌

  1. Performance Evaluation of Time Series Models using Short-Term Air Passenger Data vol.25, pp.6, 2012, https://doi.org/10.5351/KJAS.2012.25.6.917