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English

The ARIMA Time Series Analysis uses lags and shifts in the historical data to uncover patterns (e.g. moving averages, seasonality) and predict the future. The ARIMA model was first developed in the late 60s but it was systemized by Box and Jenkins in 1976.

Korean

ARIMA 시계열 분석은 패턴 (이동평균, 계절성) 을 찾고, 미래을 예측하기 위해 역사적 자료의 시차(lag) 와 추이(shift)를 사용한다 ARIMA 모델은 60년대 후반에 처음으로 개발되었으나 1976년에 Box and Jenkins에 의해 체계화되었다.