Transformations of Variables - Difference, Integrate Tab

Select the Difference, integrate tab of the Transformations of Variables dialog box to access the options described here.

Element Name Description
OK (Transform selected series) Click the OK (Transform selected series) button to transform the selected variable (series) and display a plot of the analysis. Transformed variables will be appended to the active work area. If a transformation produces an invalid value (e.g., square root of a negative value, division by zero, etc.), Statistica assigns a missing data value; then, in a second pass, those missing data are replaced according to your selection on the Time Series Analysis Startup Panel - Missing Data tab.
Transformation Use the options in the Transformation group box to select the desired type of transformation.
Differencing (x=x-x(lag)). If you select the Differencing (x=x-x(lag)) option button, the series is transformed as: x=x-x(lag), where the lag is specified in the adjacent Lag= box. After differencing, the resulting series will be of length N-lag (where N is the length of the original series).
Integrate (x=x+x(lag)) If you select the Integrate (x=x+x(lag)) option button, the series is transformed as: x=x+x(lag), where lag is specified in the adjacent Lag= box. This transformation is the reverse of differencing (see above).
Var. with leading observation. Click the Var. with leading observation button to display the Currently available variables and transformations dialog box. Use this dialog box to select a variable with the leading observations. If none is selected, then all leading observations will be equal to 0 (zero). For example, suppose the series consists of the values: 3, 4, 2, etc. We integrate the series with a lag of 1, and choose no variable with leading observations. The first value of the new series will thus be 0 (zero); the next value will be 0+3, the next 0+3+4, and so on. The resulting series will be of length N+1, where N is the number of cases in the original series. Suppose we selected a variable with leading observations, and that the value found in that series for case 1-lag (that is, in this example, for the case just preceding the first case in the series to be transformed) is equal to 5. Then the first value of the new series will be 5, the next value will be 5+3, the next 5+3+2, and so on. In this manner, you can difference a series and fully restore it to its original values by integrating it, provided you use the values of the original (untransformed) series for leading observations.