what are the differences between autoregressive and moving average models 
arima combines autoregressive features with those of moving averages an ar 1 autoregressive process for instance is one in which the current value is based on the immediately preceding value while an ar 2 process is one in which the current value is based on the previous two values a moving average is a calculation used to analyze data points by creating a series of averages of different subsets of the full data set to smooth out the influence of outliers as a result of this combination of techniques arima models can take into account trends cycles seasonality and other non static types of data when making forecasts 