What is ARIMA?
An Autoregressive Integrated Moving Average (ARIMA) model is a widely used time series forecasting technique. Autoregressive models use a linear combination of data from previous time steps to predict future values, while Moving Average models use a linear combination of past forecast errors. ARIMA models combine both of these approaches. They’re also Integrated, which means that they use the differences between data points rather than the data points themselves, in order to remove trends such as moving averages changing over time.