This enables the user to identify which lags are significantly different from zero and therefore should be included in the model for discussion. The identification stage enables the user to see if the data is stationary and therefore proceed with the Box Jenkins method. In section 1 we have identified the appropriate lags that should be used in the model. This section enables us to estimate these parameters and fit an appropriate model. However, finding the models requires consideration of parsimony and invertibility.
Parsimony is the idea of stinginess.
It basically deals with the trade off between better explanatory power and the loss of degrees of freedom. The data being invertible is also important. This means that it can be represented by a finite order or converging AR process. Here we examine whether the model that we have chosen actually fits the data. We statistically test the parameters to determine how good they are.