When can ARIMA model be used?

ARIMA Model – Manufacturing Case Study Example

ARIMA models are applied in some cases where data show evidence of non-stationarity in the sense of mean (but not variance/autocovariance) , where an initial differencing step (corresponding to the “integrated” part of the model) can be applied one or more times to eliminate the non-stationarity of the mean function ( …

ARIMA uses a number of lagged observations of time series to forecast observations . A weight is applied to each of the past term and the weights can vary based on how recent they are. AR(x) means x lagged error terms are going to be used in the ARIMA model. ARIMA relies on AutoRegression.