Differencing, Time Series Transformations

Differences the selected continuous variables, by a user-defined lag; computes a summary graph and spreadsheet of the series after differencing; autocorrelation functions can also be computed.

General

Element Name Description
Lag Specifies the lag for difference passes.
Number of passes Specifies the number of differencing passes to be computed for each series.
Creates autocorrelations Creates the autocorrelation function for the differenced series.
Number of lags Enter a value in the Number of lags box to determine the maximum number of lags for which the autocorrelations are to be computed.
Summary after last pass Creates the summary statistics after the last differencing pass only; if False, then summary results are computed after each differencing pass.
Labels plots with case names Labels the horizontal axis in plots with case numbers or case names (if available).
Generates data source, if N for input less than Generates a data source for further analyses with other Data Miner nodes if the input data source has fewer than k observations, as specified in this edit field; note that parameter k (number of observations) will be evaluated against the number of observations in the input data source, not the number of valid or selected observations.

Missing Data

Element Name Description
Replace missing data Specifies how missing data is to be replaced. Missing data can be replaced by the overall mean, interpolated from adjacent points, replaced by the mean or median of N adjacent points (on both sides of the hole), or estimated (predicted) from linear trend regression. Note that as long as the missing data are at the end of the series (trailing missing data) or the beginning of the series (leading missing data), the missing data will simply be ignored.
Number of adjacent points Applicable if missing data are replaced by the mean or median of N adjacent points; specify N. The missing data are replaced by the mean or median computed from the N adjacent points on both sides of the hole of missing data.