Single Series ARIMA Results - Distribution of Residuals Tab

Select the Distribution of Residuals tab of the Single Series ARIMA Results dialog box to access the options described here.

Element Name Description
Plot of residuals Use the options in the Plot of residuals group box to plot residuals in order to review the distribution of the ARIMA residuals. Note that the residuals are computed for the transformed and differenced series, and thus they may be different than those that can be computed via the Forecasting options on the Advanced tab. The ARIMA model assumes that the residuals (random shock component of the model: ε) are normally distributed. Quick visual checks of the validity of this assumption can be performed via these plots.
Histogram Click the Histogram button to display a histogram for the residuals with the normal distribution curve superimposed.
Normal probability plot Click the Normal probability plot button to display a normal probability plot of the residuals. The way the standard normal probability plot is constructed is as follows. First the values are rank ordered. From these ranks we can compute z values (i.e., standardized values of the normal distribution) based on the assumption that the data come from a normal distribution. These z values are plotted on the y-axis in the plot. If the residuals (plotted on the x-axis) are normally distributed, then all points should fall onto a straight line in the plot. If the residuals are not normally distributed, they will deviate from the line. Outliers may also become evident in this plot.
Detrended normal probability plot Click the Detrended normal probability plot button to display a detrended normal probability plot, which is constructed in the same way as the standard normal probability plot, except that before the plot is produced, the linear trend is removed. This often "spreads out" the plot, thereby allowing the user to detect patterns of deviations more easily.
Half normal probability plot Click the Half normal probability plot button to display a half-normal probability plot, which is constructed in the same way as the standard normal probability plot, except that only the positive half of the normal curve is considered. Consequently, only positive normal values will be plotted on the y-axis.