Time Series Analysis

ARIMA model (moving average autoregressive model), its the most common method of time series forecasting analysis. ARIMA model can be split into 3 items, namely AR model, I i.e. difference, and MA model. SPSSAU intelligently finds out the best AR model, I i.e. difference, and MA model, and finally gives the best model prediction result, the principle of SPSSAU intelligently finding out the best model lies in the use of the rule of minimizing the value of the AIC, iterating through various possible model combinations for model construction, and combining with the rule of minimizing the value of the AIC, the model is constructed by using the AIC. The principle of SPSSAU to find out the best model is to use the rule of minimum AIC value to traverse all possible model combinations to construct the model, and combined with the rule of minimum AIC, finally get the best model.

Of course, researchers can also set up the AR model, differential order and MA model by themselves, i.e., set up the autoregressive order p, the differential order d and the moving average order q respectively, and then carry out the model construction. As to what the appropriate values of autoregressive order p, differential order d and moving average order q should be set, it is recommended that researchers analyze them using partial (auto-)correlation plots (SPSSAU also intelligently provides the suggestion of p or q values) and analyze them using the ADF test to derive the appropriate value of differential order d (SPSSAU also intelligently provides the suggestion of the optimal value of differential order d), respectively.

The ARIMA model can be split into 3 items, which are AR model, I i.e., difference, and MA model. sPSSAU intelligently finds out the best AR model, I i.e., difference, and MA model. Of course, if the researcher sets the AR model, difference order and MA model by himself, i.e., sets the autoregressive order p, difference order d value and moving average order q respectively, at this time SPSSAU constructs the model according to the researcher's settings. It is recommended that users can directly use the intelligent analysis of SPSSAU.

SPSSAU operates as follows: