Time Series Data Transformations

Several data transformations that are useful in time series analysis are provided:

• Generate date variables to establish periodicity and to distinguish between historical, validation, and forecasting periods.
• Create new time series variables as functions of existing time series variables.
• Replace system- and user-missing values with estimates based on one of several methods.

A time series is obtained by measuring a variable (or set of variables) regularly over a period of time. Time series data transformations assume a data file structure in which each case (row) represents a set of observations at a different time, and the length of time between cases is uniform.