[Back]

A. Kowarik, A. Meraner, M. Templ, D. Schopfhauser:
"Seasonal Adjustment with the R-packages x12 and x12GUI";
Journal of Statistical Software, 62 (2014), 2; 1 - 21.

The \proglang{X-12-ARIMA} Seasonal Adjustment program of the
U.S.
Census Bureau extracts the different components (mainly: seasonal component, trend component, outlier component and
irregular component) of a monthly or quarterly time series.
It is the state-of-the-art technology for seasonal adjustment
used in many statistical offices. It is possible to include a moving holiday
effect, a trading day effect and user-defined regressors, and additionally
incorporates automatic outlier detection.
The procedure makes additive or multiplicative adjustments and creates an output
data set containing the adjusted time series and intermediate calculations.

The original output from \proglang{X-12-ARIMA} is somehow static and it is not
always an easy task for users to extract the required information for further processing.
The \proglang{R}-package \pkg{x12} provides wrapper functions and an abstraction
layer for batch processing \proglang{X-12-ARIMA}.
It allows summarizing, modifying and storing
the output from \proglang{X-12-ARIMA} within a well-defined class-oriented
implementation.

On top of the class-oriented (command line) implementation the
graphical user interface allows access to the
\proglang{R}-package \pkg{x12} without demanding too much \proglang{R}
knowledge.
Users can interactively select
additive outliers, level shifts and temporary changes and see the impact
immediately.

Having the powerful \proglang{X-12-ARIMA} Seasonal Adjustment program available
directly from within \proglang{R}, as well as containing the new facilities for
marking outliers, batch processing and change tracking, makes the package a potent and functional tool.

time series, seasonal adjustment, outlier detection, R

http://www.jstatsoft.org/v62/i02/paper