최적 시계열 수요예측 모델선정에 관한 연구

• 영문명: Selecting Most Appropriate Time Series Forecasting Model
• 발행기관: 한국관광학회
• 저자명: 李忠基 宋學俊
• 간행물 정보: 『관광학연구』제31권 제6호, 289~311쪽, 전체 23쪽
• 주제분류: 사회과학 > 관광학
• 파일형태: PDF
• 발행일자: 2007.12.31

영문 초록

This study aims to develop four time-series models in order to select the best model among the time-series models based on MAPE(mean absolute percentage error). The time-series models include various ones including ARIMA model. The first three models have been most popularly used for forecasting tourism demand, whereas the last model of ARIMA Intervention is reported to be more logical and accurate than any other time-series models since special events such as terrorism and mega-events can be incorporated into the model. The results of model estimation indicate that all the four forecasting models were found most accurate in terms of MAPE(Lewis, 1982). Of them the ARIMA Intervention model(MAPE=4.48) appeared to perform best in terms of forecasting accuracy, followed by ARIMA(MAPE=4.96), Winters(5.67), and Stepwise Autoregressive(8.55).

목차

I. 서론

II. 선행연구 검토

III. 연구방법

IV. 분석결과

V. 결론

참고문헌

키워드

예측정확도 윈터스지수평활모델 단계적 자기회귀모델 ARIMA모델 ARIMA 개입모델 Forecasting accuracy Winters Exponential Smoothing model Stepwise Autoregressive model ARIMA model ARIMA Intervention model