Introduction - If you have any usage issues, please Google them yourself
The ARIMA model uses a mathematical model to approximate the sequence of data by forming a sequence of data that is predicted over time. It is divided into AR, MA, ARMA and ARIMA processes according to the stability of the original sequence and the included part of the regression.
In the process of the model according to the autocorrelation function, the partial sequence of stationary sequence autocorrelation function of discrimination; and for non stationary sequences generally need treatment to convert it into stationary sequence by difference (ARIMA); for the stationary sequences obtained were modeled to determine the best model (AR ARMA, MA, or ARIMA). In use, the most important and most important is to estimate the parameters of the sequence to test whether it is statistically significant.