The X11 procedure provides seasonal adjustment of time series by using the Census X-11 or X-11 ARIMA method. The X11 procedure is based on the U.S. Bureau of the Census X-11 seasonal adjustment program and also supports the X-11 ARIMA method developed by Statistics Canada. The X11 procedure includes the following features:

• decomposition of monthly or quarterly series into seasonal, trend, trading day, and irregular components

• both multiplicative and additive form of the decomposition

• all the features of the Census Bureau program

• support of the X-11 ARIMA method

• support of sliding spans analysis

• processing of any number of variables at once with no maximum length for a series

• computation of tests for stable, moving, and combined seasonality

• optional printing or storing in SAS data sets of the individual X11 tables that show the various components at different stages of the computation; full control over what is printed or output

• ability to project seasonal component one year ahead, which enables reintroduction of seasonal factors for an extrapolated series

The X12 procedure provides seasonal adjustment of time series using the X-12 ARIMA method. The X12 procedure is based on the U.S. Bureau of the Census X-12 ARIMA seasonal adjustment program (version 0.3). It also supports the X-11 ARIMA method developed by Statistics Canada and the previous X-11 method of the U.S. Census Bureau. The X12 procedure includes the following features:

• decomposition of monthly or quarterly series into seasonal, trend, trading day, and irregular components

• support of multiplicative, additive, pseudo-additive, and log additive forms of decomposition

• support of the X-12 ARIMA method

• support of regARIMA modeling

• automatic identification of outliers

• support of TRAMO-based automatic model selection

• use of regressors to process missing values within the span of the series

• processing of any number of variables at once with no maximum length for a series

• computation of tests for stable, moving, and combined seasonality

• spectral analysis of original, seasonally adjusted, and irregular series

• optional printing or storing in a SAS data set of the individual X11 tables that show the various components at different stages of the decomposition; full control over what is printed or output

• optional projection of seasonal component one year ahead, which enables reintroduction of seasonal factors for an extrapolated series