계층적 시계열 분석을 이용한 지역별 교통사고 발생건수 예측

Hierarchical time series forecasting with an application to traffic accident counts
Citations

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초록

The paper introduces bottom-up and optimal combination methods that can analyze and forecast hierarchical time series. These methods allow forecasts at lower levels to be summed consistently to upper levels without any ad-hoc adjustment. They can also potentially improve forecast performance in comparison to independent forecasts. We forecast regional traffic accident counts as time series data in order to identify efficiency gains from hierarchical forecasting. We observe that bottom-up or optimal combination methods are superior to independent methods in terms of forecast accuracy.

키워드

grouped time series; revised forecasts; bottom-up forecasts; optimal combination forecasts; ARIMA model; exponential smoothing method
제목
계층적 시계열 분석을 이용한 지역별 교통사고 발생건수 예측
제목 (타언어)
Hierarchical time series forecasting with an application to traffic accident counts
저자
이주은; 성병찬
DOI
10.5351/KJAS.2017.30.1.181
발행일
2017-02
유형
Article
저널명
응용통계연구
권
30
호
1
페이지
181 ~ 193