자기회귀누적이동평균 ARIMA

1 개요

autoregressive integrated moving average (ARIMA), ARIMA model

자기회귀 누적이동평균, 자기회귀 누적이동평균 모형, ARIMA 모형

• 자기회귀이동평균(ARMA) 모형의 일반화

2 예시

Some well-known special cases arise naturally or are mathematically equivalent to other popular forecasting models. For example:

• An ARIMA(0, 1, 0) model (or I(1) model) is given by [math]\displaystyle{ X_t = X_{t-1} + \varepsilon_t }[/math] — which is simply a random walk.
• An ARIMA(0, 1, 0) with a constant, given by [math]\displaystyle{ X_t = c + X_{t-1} + \varepsilon_t }[/math] — which is a random walk with drift.
• An ARIMA(0, 0, 0) model is a white noise model.
• An ARIMA(0, 1, 2) model is a Damped Holt's model.
• An ARIMA(0, 1, 1) model without constant is a basic exponential smoothing model.
• An ARIMA(0, 2, 2) model is given by [math]\displaystyle{ X_t = 2X_{t-1} - X_{t-2} +(\alpha + \beta - 2) \varepsilon_{t-1} + (1-\alpha)\varepsilon_{t-2} + \varepsilon_{t} }[/math] — which is equivalent to Holt's linear method with additive errors, or double exponential smoothing.

3 같이 보기

• ARIMA(1, 0, 0)
• ARIMA(0, 1, 0)
• ARIMA(1, 1, 0)
• ARIMA(0, 1, 1)
• 자기회귀
• X-12-ARIMA
• 편자기상관함수
• 자기회귀이동평균 ARMA
• R arima()

4 참고

• 영어 위키백과 "Autoregressive integrated moving average"
• 다음백과 "ARIMA"
• 네이버백과 "ARIMA"