Subsections:

This section discusses aspects of storing time series in SAS data sets. The topics discussed are the standard form of a time series data set, storing several series with different time ranges in the same data set, omitted observations, cross-sectional dimensions and BY groups, and interleaved time series.

Any number of time series can be stored in a SAS data set. Normally, each time series is stored in a separate variable. For example, the following statements augment the USCPI data set read in the previous example with values for the producer price index:

data usprice; input date : monyy7. cpi ppi; format date monyy7.; label cpi = "Consumer Price Index" ppi = "Producer Price Index"; datalines; jun1990 129.9 114.3 jul1990 130.4 114.5 aug1990 131.6 116.5 ... more lines ...

proc print data=usprice; run;

Figure 3.4: Time Series Data Set Containing Two Series

Obs | date | cpi | ppi |
---|---|---|---|

1 | JUN1990 | 129.9 | 114.3 |

2 | JUL1990 | 130.4 | 114.5 |

3 | AUG1990 | 131.6 | 116.5 |

4 | SEP1990 | 132.7 | 118.4 |

5 | OCT1990 | 133.5 | 120.8 |

6 | NOV1990 | 133.8 | 120.1 |

7 | DEC1990 | 133.8 | 118.7 |

8 | JAN1991 | 134.6 | 119.0 |

9 | FEB1991 | 134.8 | 117.2 |

10 | MAR1991 | 135.0 | 116.2 |

11 | APR1991 | 135.2 | 116.0 |

12 | MAY1991 | 135.6 | 116.5 |

13 | JUN1991 | 136.0 | 116.3 |

14 | JUL1991 | 136.2 | 116.0 |