ARIMA预测模型，ARIMA模型全称为自回归移动平均模型(Autoregressive Integrated Moving Average Model,简记ARIMA)，是由博克思(Box)和詹金斯(Jenkins)于70年代初提出的一著名时间序列预测方法，所以又称为box-jenkins模型、博克思-詹金斯法。其中ARIMA（p，d，q）称为差分自回归移动平均模型，AR是自回归, p为自回归项; MA为移动平均，q为移动平均项数，d为时间序列成为平稳时所做的差分次数。
ARIMA model is called autoregressive integrated moving average model (ARIMA). It is a famous time series prediction method put forward by box and Jenkins in the early 1970s, so it is also called box Jenkins model and boxjenkins method. ARIMA (P, D, q) is called differential autoregressive moving average model, AR is autoregressive, P is autoregressive; Ma is moving average, q is moving average, and D is the difference times when time series becomes stable. (2020-05-29, R language, 1KB, 下载0次)