X-13ARIMA-SEATS Seasonal Adjustment Program

X-13-Graph: A SAS/GRAPH^® Program for X-13ARIMA-SEATS Output
User's Guide for the Batch Program on the PC or Unix, Version 2.0

Demetra Lytras, U.S. Census Bureau

Primary Developer: Catherine C. Harvill Hood

May 22, 2012

This document explains how to use the Batch Version of the X-13-Graph application. It includes the following topics:

• 1: New Features in X-13-Graph
• 2: Installing X-13-Graph
  • 2.1: Requirements for the Program
  • 2.2: Installing X-13-Graph
• 3: Instructions for Running X-13-Graph in Batch Mode
  • 3.1: Running X-13ARIMA-SEATS in Graphics Mode
  • 3.2: Additional Files Needed
    • 3.2.1: The Graph List (.gls) File
    • 3.2.2: The Graphics Metafile List (.mls) File
  • 3.3: Running the Batch Program
  • 3.4: Important Things to Remember
  • 3.5: Global Options in the Batch Program
    • 3.5.1: Subspans
    • 3.5.2: Graph Colors
    • 3.5.3: Line Types and Widths
    • 3.5.4: Subtitles, Footnotes, and Labels
    • 3.5.5: Fonts
    • 3.5.6: Y-Axis Options
    • 3.5.7: Reference Gridlines
    • 3.5.8: Noting Trend Uncertainty
    • 3.5.9: Component Graph Formats
• 4: Details of Graphs Available in X-13-Graph Batch
  • 4.1: Overlay Graphs
  • 4.2: Spectrum Graphs
  • 4.3: Component Graphs
  • 4.4: Special Seasonal Factor Graphs
  • 4.5: Forecast Graphs
  • 4.6: History Graphs
  • 4.7: ACF/PACF Graphs
  • 4.8: Outlier T-Value Graphs
  • 4.9: First Difference Graphs
  • 4.10: Year on Year Graphs
  • 4.11: Sliding Spans Graphs
  • 4.12: SEATS Filter and Diagnostic Graphs
  • 4.13: Power Graphs
  • 4.14: Overlay Graphs for Comparing Two Series
  • 4.15: Component Graphs for Comparing Two Series
  • 4.16: History Graphs for Comparing Two Adjustments
  • 4.17: SI Ratio Graphs for Comparing Two Adjustments
  • 4.18: Forecast Graphs for Comparing Two Adjustments
  • 4.19: Spectrum Graphs for Comparing Two Adjustments
  • 4.20: Seasonal Factor by Month Graphs for Comparing Two Adjustments
• 5: Examples
• 6: Reporting Problems
• 7: Acknowledgements
• 8: References
• Appendix A

1: New Features in X-13-Graph

X-13-Graph Batch 2.0 follows X-13-Graph Batch Version 1.6. It contains all the same graphs and options as that program, and adds to it sliding spans graphs, seasonal factor by month graphs to compare two adjustments, and a number of graphs of SEATS filters, their squared gains and time shifts, and other SEATS diagnostic graphs.

The version also includes various bug fixes.

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2: Installing X-13-Graph

2.1: Requirements

X-13-Graph Batch is a SAS^® program using SAS/GRAPH^® (SAS Institute, Inc. 1990). It requires SAS Version 8 or higher. The program also requires X-13ARIMA-SEATS or Version 0.2.8 or higher of X-12-ARIMA.

No knowledge of SAS is required to use X-13-Graph. A Windows interface is available for X-13-Graph Batch.

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2.2: Installing X-13-Graph

Before you can use X-13-Graph, you must copy it to your computer:

1. Create a directory for the program; c:\x13graph is recommended, and will be used throughout this document.
2. Copy the file x13gbat.zip to the c:\x13graph directory.
3. Double Click on x13gbat.zip in Windows^® Explorer to uncompress the files.

X-13-Graph Batch consists of a SAS program, a subdirectory with two SAS files, and an images subdirectory, as well as this document. After uncompressing x13gbat.zip, the following files should be in the c:\x13graph directory:

x13gbat.sas
x13gbat.htm

The c:\x13graph\appl directory should contain the following files:

Namelist.sas7bdat
Templt.sas7bcat

There should also be a directory c:\x13graph\images containing examples of the graphs that can be created.

The two SAS files in the appl subdirectory must be in that directory for the program to run. The SAS program x13gbat.sas can be stored in any directory.

SAS and SAS/GRAPH software are registered trademarks of the SAS Institute Inc. in the USA and other countries. ^® indicates USA registration.

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3: Instructions for Running X-13-Graph in Batch Mode

3.1: Running X-13ARIMA-SEATS in Graphics Mode

Before you can create any graphs with X-13-Graph, you must run X-13ARIMA-SEATS in graphics mode to produce the necessary output files. Running X-13ARIMA-SEATS in graphics mode creates graphics files corresponding to the X-13ARIMA-SEATS options you specified in the .spc file. X-13ARIMA-SEATS also creates a graphics metafile, identified by the extension .gmt, which contains a list of all the graphics output files produced during the X-13ARIMA-SEATS run.

If you run X-13ARIMA-SEATS from an interface like Win X-13, make sure the appropriate option to run in graphics mode is selected. If you run X-13ARIMA-SEATS from the command prompt, you must provide the name of an existing directory after the flag -g; X-13ARIMA-SEATS will store all graphics files in this specified directory. Because of output filename conflicts, this must be a different directory from where other output files are created. For example, when running X-13ARIMA-SEATS with the command

x13a bshors -g c:\x13a\graphics,

the graphics output files for the series bshors will be stored in the directory c:\x13a\graphics. (For more information, see Section 2.7 of the X-13ARIMA-SEATS Reference Manual (U.S. Census Bureau 2012).)

If you have an interface for X-13ARIMA-SEATS, make sure to select the option to run the program in graphics mode.

To obtain graphs for several different series from a single run of this batch program, you must run X-13ARIMA-SEATS in graphics mode with the same directory after the -g option for each series.

Note: The SAS program uses the title statement from the X-13ARIMA-SEATS run to assign secondary titles to the graphs. This allows you to assign meaningful titles to the graphs within the X-13ARIMA-SEATS .spc file. If you are creating graphs for one series at a time, you can also use the subtitle option to assign a subtitle to the graph. Details are given in Section 3.5.4.

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3.2: Additional Files Needed

You will need two additional files to run X-13-Graph: a graph list file, identified by the extension .gls, and a graphics metafile list, identified by the extension .mls. Both files must have the same filename. (The default input filenames in the batch program are x13g.gls and x13g.mls, but these can be changed.)

The graph list file and the graphics metafile list file both must be in the directory specified after the -g option in the X-13ARIMA-SEATS runs.

3.2.1: The Graph List (.gls) File

The graph list file is a list of commands telling the program which graphs to produce.

The basic format of a command in the graph list file is

keyword: element1 <element2 <element3 <element4>>>

The keyword tells the program which type of graph to produce and the elements tell the program which graphical elements to include in the graph.

Important: The keyword must be followed by a colon.

The current version of the program can produce fourteen types of graphs for each series, and seven types of graphs to compare two different series or adjustments.

Graph Types and Keywords

Graph Type	Keyword
Overlay Graphs	overlay
Spectrum Graphs	spectrum
Component Graphs	cmpnent
Special Seasonal Graphs	seas
Forecast Graphs	forecast
History Graphs	history1
ACF/PACF graphs	acfpacf
Sliding Spans Graphs	sspans
Outlier T-Value Graphs	tvalue or abtvalue
First Difference Graphs	fstdiff
Year-on-Year Graphs	yronyr
SEATS Filter, Time Shift, and Squared Gain Graphs	filter
SEATS Diagnostic Graphs	seats
Power Graphs	power
Overlay Graphs for Two Series	overlay2
Component Graphs for Two Series	cmpnent2
History Graphs for Two Adjustments	history2
SI Ratio Graphs for Two Adjustments	rsi2
Forecast Graphs for Two Adjustments	fcast2
Spectrum Graphs for Two Adjustments	spect2
Seasonal Overlay Graphs	seas2

Examples of graphical elements are the original series, the trend components, the seasonal factors, etc. A list of all possible elements for each type of graph is given in the Details section. With a few exceptions, they have the same abbreviations used by X-13ARIMA-SEATS in the graphics metafile (.gmt). These exceptions are given in Appendix A.

You must give at least one element for each keyword specified, but no more than four elements for each line. The keywords and elements must be on the same line.

You can put many different commands in the graph list file, but each command must be on a separate line. You can ask for a certain type of graph more than once with different elements each time.

For example, to graph the original series by itself, the seasonally adjusted series superimposed with the trend, spectrum plots of both the original series and the seasonally adjusted series, the seasonal factors by month, a component plot for the seasonal factors and the irregular, and a forecast graph on the transformed scale, you would need the following seven commands in the graph list file.

overlay: ori
overlay: sa trn
spectrum: spcori spcsa
seas: sf
cmpnent: sf irr
forecast: ftr

You can add comment lines, or comment out keywords and the associated options, by putting a # sign in the first column of the line.

The elements you choose should correspond to elements that are available for every series you want to graph. For example, if you ask for a graph of the outlier-adjusted series, there will be an error for every series that does not have an outlier-adjusted series.

The format of the command for overlay graphs for comparing two series and seasonal factor by month graphs for comparing two series is slightly different. See Section 4.14 or Section 4.20 for details.

3.2.2: The Graphics Metafile List (.mls) File

The graphics metafile list file is a list of the series you want to graph. Each series should be listed at the beginning of a separate line, except when comparing two models.

If you want to compare two models using the overlay, component, history, or rsi graphs for two adjustments, then you must enter the names of the two series on the same line in the .mls file. This will produce the comparison graphs you request in the .gls file; additionally, all the remaining graphs you request will be produced for each series as if they had been entered on separate lines. Again, you can add comment lines or comment out series by putting a # sign in the first column of the line.

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3.3: Running the Batch Program

Once X-13ARIMA-SEATS has been run in graphics mode and the .gls and .mls files have been created, you can run X-13-Graph:

1. Open the SAS system on your operating system. (For example, in Windows, double-click on the SAS icon.)
   
2. Open the X-13-Graphics Batch program, x13gbat.sas, either by clicking on the open file button or by using the File pull-down menu.
   
3. Change the SAS libname, default device name, default input filenames, the default graphics directory, and the number of graphs printed on a page, as needed.

   Note: SAS uses semicolons to end commands. Each line must end with a semicolon.

   1. SAS Libname

      Enter the name of the directory where X-13-Graph is installed where the program reads:

      %let x13gappl = c:\x13graph\appl;

      Typically, the directory would be c:\x13graph\appl on a PC.

   2. Device Name

      Enter the device name of your printer where the program reads:

      %let devname = WIN ;

      Setting the device equal to WIN will send the graphs to the screen. Printer device names depend on the printer used. For example, the SAS device name for a LaserJet 5SI PostScript printer is LJ5SIPS. So to print the graphs on a LaserJet 5SI PostScript printer, this line 26 should read:

      %let devname = LJ5SIPS ;

      To see a list of available SAS devices:

      1. Go to the command line. This is the text entry area on the tool bar, usually at the left side. Enter the command dir sashelp to bring up the Directory Window.
         
      2. Double click on the catalog called DEVICES This brings up a list of all the SAS devices available for your version of SAS.

         Note: If you are sending the output to a printer, you should disable banner pages before you begin if possible. SAS sends each graph to the printer separately.

   3. Input Filenames

      Enter the filename of the graph list file and the graphics metafile list file where the program reads:

      %let inptfile = x13g ;

      For example, if you have named the input files allx13g.gls and allx13g.mls then this line should read:

      %let inptfile = allx13g ;

   4. Graphics Directory

      Enter the name of the graphics directory where the program reads

      %let inptdir = c:\x13a\graphics\ ;

      The graphics directory is the directory that was specified after the -g option in the X-13ARIMA-SEATS runs.

   5. Number of Graphs Per Page

      Enter the number of graphs you want printed on each page where the program reads:

      %let perpage=1;

      The only values allowed are 1, 2, or 3.

      Note: All the graphs for one series print, then all the graphs for the next, and so on. If you specify two graphs to print per page, but ask for three graphs for each series, then the third graph for the first series will be on the same page as the first graph for the second series.

4. Once you have made any necessary changes, run x13gbat.sas by clicking the Submit button (the person running) or selecting Submit from the Run pull-down menu.

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3.4: Important Things to Remember

The two input files (the graph list file and the graphics metafile list file) must have the same filename, specified in x13gbat.sas by the inptfile variable.

X-13ARIMA-SEATS must be run in graphics mode with the same directory specified by the -g option for each series listed in the graphics metafile list file. This directory is specified in x13gbat.sas by the inptdir variable. The two input files (the graph list file and the graphics metafile list file) must also be in this directory.

X-13-Graph can only create graphs if the required graphics file was produced by X-13ARIMA-SEATS. Make sure that you run X-13ARIMA-SEATS with the necessary spec or option to create the files you want.

Each keyword in the graph list file must be followed by a colon and then by at least one element. A keyword and its elements must be on the same line. Each command must be on a separate line.

When modifying the SAS program, remember to end each line with a semicolon.

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3.5: Global Options in the Batch Program

There are many options available to customize the appearance of the graphs. This is done by changing the value of certain variables which appear at the top of the program. All these variables appear in the first hundred lines of the X-13-Graph Batch program, before the section "Instructions for setting macro variables." Many of these variables are case-sensitive, so follow the instructions for setting them carefully. Also, make certain that each variable definition is followed by a semicolon; the SAS program will not run correctly if there is a missing semicolon.

3.5.1: Subspans

By default, the batch program graphs all available years. To see a shorter span of the series, change the values of substart and subend in the x13gbat.sas program, which read:

%let substart = year.mon;
%let subend = year.mon;

Substart is the year and month (or quarter) of the beginning of the desired subspan; subend denotes the end of the subspan. If the value entered is blank or outside the span of the series, the program will default back to the original dates. All dates are in X-13ARIMA-SEATS date format, yyyy.mon, yyyy.mm, or yyyy.q (that is, 2006.Feb, 2006.02, or 2006.1).

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3.5.2: Graph Colors

To change the colors of the graphs and the labels, use the color0 through color6 and colorg variables in the program, which read:

%let color0 = black;
%let color1 = blue;
...
%let color6=red;
%let colorg = black;

Color0 is the color of the graph text: that is, the titles, subtitles, labels, graph values, and footnotes. The default color is black. Color1 through color6 give the colors of the graphs. In graphs with more than one element superimposed, the first is assigned color1, the second color2, and so on. In some graphs, certain gridlines are also assigned these colors. The remainder of the gridlines are assigned the color specified in the variable colorg.

Some options for colors are black, blue, green, red, orange, yellow, pink, purple, magenta, gray, brown, or cyan.

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3.5.3: Line Types and Widths

The line types and widths of the graphs can be changed using the variables ltype1 through ltype6 and lw1 through lw6; the line type of most gridlines can be changed using ltypeg. In graphs with more than one element superimposed, the first is assigned line ltype1 with width lw1, the second ltype2 with width lw2, and so on.

Line types are assigned using a number between 1 and 46; each number requests a specific pattern. The X-13-Graph Batch program supports the following line types:

Other line types available in SAS can be used, but the footnotes in the overlay graphs will not show the correct line when they are used.

The width of the line is a number, usually 1 or 2. The line becomes thicker as the number increases.

The default setting for line types and widths is:

%let ltype1 = 1;
%let ltype2 = 21;
%let ltype3 = 41;
%let ltype4 = 14;
%let ltype5 = 20;
%let ltype6 = 26;
%let ltypeg = 35;
%let lw1 = 2;
...
%let lw6 = 2;

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3.5.4: Subtitles, Footnotes, and Labels

The main title of each graph denotes what is being plotted; the graph's subtitle tells which series is being plotted. By default, the subtitle is the title given in the series spec of the .spc file before it is run with the X-13ARIMA-SEATS program. If a title is not supplied, the default subtitle is the series name. However, the subtitle can be changed using the variables subtitle and subtitle2.

If these variables are left blank, the default subtitles will be used. Otherwise, the value of subtitle is used for the first series plotted and the value of subtitle2 is used for the second series for the overlay, component, and history graphs for two adjustments. The subtitle requested should be between the equal sign and the semicolon; quotation marks are not needed. The following is a valid assignment:

%let subtitle=Construction Starts Through 2005;

Use ftnoteyn to instruct the program not to print footnotes for overlay, forecast, seasonal, spectrum, tvalue, and history graphs, and not to print axis labels for all graphs. When this variable is set to

%let ftnoteyn=no;

the footnotes and graph labels are not printed; otherwise, they are.

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3.5.5: Fonts

The font used for the title and subtitle can be changed using the variable font1, and that of the labels and footnotes can be changed with font2. There are not many fonts available in SAS; a complete list can be found in the catalog Sashelp.Fonts, or using the SAS Help. Some available fonts are:

The default font, used if no font is entered or if the font chosen is not valid, is Swiss.

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3.5.6: Y-Axis Options

The values on the y-axis can be changed in two ways: the range of values can be specified, and the values can be scaled by a requested divisor.

To change the range of the graph, a value must be supplied for both the variables yaxmin and yaxmax, the minimum and maximum y-value to be plotted. If desired, a value can also be provided for yaxby, which is used to increment the values. If this variable is left blank, the program will create the increment automatically. If these variables are set to:

%let yaxmin=2000;
%let yaxmax=8000;
%let yaxby=2000;

then the y-axis will have tick marks at values 2000, 4000, 6000, and 8000. Note that if no tick mark created with yaxby falls on yaxmax, then the maximum y-value will be the largest tick mark less than yaxmax. That is, if yaxmin is 2000, yaxmax is 8000, and yaxby is 2500, the y-axis will have tick marks at 2000, 4500, and 7000. The y-axis will not go all the way to 8000.

To scale the y-axis by a divisor, change the value of the variable ydivisor. For example, if the data ranges from two million to six million, then

%let ydivisor=1000000;

will divide the y-variable by one million, so the y-axis will range from two to six, and will also create the label 'In Millions' for that axis unless the ftnoteyn variable is set to 'N'. If the y-divisor is not a power of ten, then the label will read 'Units=ydivisor.' This label will be printed sideways along the y-axis unless the variable anglelabel is changed to no:

%let anglelabel=no;

In this case, the label will be printed at the top of the y-axis.

If both a change in the range and a change of scale are requested, then the values requested for the y-axis maximum and minimum should be in the original scale.

These options are available for most graphs. However, neither are available for component graphs, seasonal si graphs, or outlier t-value graphs, and the y-divisor option is not available for any element on the log scale, spectrum graphs, seasonal graphs, and seasonal factor history graphs.

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3.5.7: Reference Gridlines

By default, the program automatically creates a reference line at the first month or quarter of the graph. To move the reference lines to another month or quarter in order to highlight some particular month, change the variable gridlinemo. For example,

%let gridlinemo = 7;

will put reference lines at July, if it is a monthly series. The color and style of this reference line can be changed with the variables colorg and ltypeg, as described in Sections 3.5.2 and 3.5.3. A label will automatically be added to the graph indicating which month or quarter the gridline represents unless the ftnoteyn variable is set to no. Note that if the variable gridlinemo is left blank, the reference line will be at the first month or quarter but no label will be included; if the variable gridlinemo is set to 1, then the label 'Gridlines at January' will be added to the graph.

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3.5.8: Noting Trend Uncertainty

When plotting the trend with overlay or overlay2 graphs, you can emphasize the uncertainty of the last few trend estimates by plotting an 'X' for a specified number of points using the variable numtrendx. For example, the assignment

%let numtrendx=3;

would result in the following trend graph:

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3.5.9: Component Graph Formats

When more than one element is requested for the component graphs, the program prints all the requested graphs on one page. If there are two elements, the graphs are printed with the second graph below the first. If there are four elements, the graphs are printed in two columns with two rows each. If there are three elements, the format used to print the graphs can be changed. By default, the program prints the graphs in two rows, with the first two graphs on top and the third below the first, as such:

The variable comp3format can be used to change the format, printing the three graphs in one column with three rows, as such:

This can be done by letting comp3format equal V3S:

%let comp3format = V3S;

Return to Component Graphs.

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4: Details of Graphs Available in X-13-Graph Batch

The current version of the program can produce the following types of graphs for each series: overlay graphs, spectrum graphs, component graphs, special seasonal factor graphs, forecast graphs, history graphs, ACF/PACF graphs, outlier t-value graphs, first difference graphs, year on year graphs, power graphs. It can also produce overlay graphs, component graphs, history graphs, and rsi graphs for comparing two adjustments.

4.1: Overlay Graphs

You can select from one to three different graphical elements to plot above a single axis. The program superimposes the elements. The order in which the elements are listed determines the order of the names in the title and legend and also the color and line used for each element. The keyword for overlay graphs is overlay.

If any of the elements requested does not exist for a series, then that graph will not be created. For example, if the statement

overlay: oadori trn sa

is in the .gls file, and the series has no outliers, and thus no outlier-adjusted series, then the entire graph will not be created, even if the seasonally adjusted series and the trend component exist.

Note: For overlay graphs, choose series on the same scale, i.e., do not choose elements on the original scale and the log scale. If elements on the original scale and the log scale are requested,the graph will not be created.

Available Elements for Overlay Graphs

Element	Element Code
Original or Composite Series	ori
Calendar-Adjusted Original Series	cad
Original Data with Preliminary Adjustments	priadj
Original Series Modified for Extremes	mori
Original Series with Replaced Missing Values	mvadj
Original Series Showing Additive Outlier Adjustments	oriao
Outlier Adjusted Original or Composite Series	oadori
Prior Adjusted Original Series	adjori
Seasonally Adjusted Series	sa
Seasonally Adjusted Series with Annual Totals	satot
Seasonally Adjusted Series Modified for Extremes	msa
Trend	trn
Indirect Seasonal Adjustment	indsa
Indirect Seasonally Adjusted Series with Annual Total	indsat
Original Modified for Extremes from Indirect	indmor
Seasonally Adjusted Series Modified for Extremes from Indirect	indmsa
Composite Series Adjusted by Prior Factors	cmppadj
Indirect Trend	indtrn
Log of Original (or Composite) Series	lori
Log of Calendar-Adjusted Original Series	lcad
Log of Original Data with Preliminary Adjustments	lpriadj
Log of Original Series Modified for Extremes	lmori
Log of Original Series Showing AO Adjustments	loriao
Log of Original with Replaced Missing Values	lmvadj
Log of Outlier Adjusted original (or Composite)	loadori
Log of Prior Adjusted Original Series	ladjori
Log of Seasonally Adjusted	lsa
Log of Seasonally Adjusted Series Modified for Extremes	lmsa
Log of Seasonally Adjusted with Annual Totals	lsatot
Log of Trend	ltrn
Log of Indirect Seasonal Adjustment	lindsa
Log of Indirect Seasonally Adjusted Series with Annual Total	lindsat
Log of Indirect Trend	lindtrn
Log of Original Modified for Extremes from Indirect	lindmor
Log of Seasonally Adjusted Series Modified for Extremes from Indirect	lindmsa
Log of Composite Series Adjusted by Prior Factors	lpacmp

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4.2: Spectrum Graphs

Graphs of 10 times the log₁₀ of the spectrum amplitudes are similar to those in the X-13ARIMA-SEATS .out file. The keyword for spectrum graphs is spectrum.

Vertical lines identify the amplitudes at seasonal and trading day frequencies. Cleveland and Devlin (1980) identified the trading day frequencies of this graph as the frequencies most likely to have spectral peaks if a flow series has a trading day component. Note that the color and line type of these reference lines are not controlled with the colorg and ltypeg options, but rather seasonal frequencies use the color2 and ltype2 variables, while trading day frequencies use the color3 and ltype3 variables.

Available Elements for Spectrum Graphs

Element	Element Code
Spectrum of the Original Series	spcori
Spectrum of the Seasonally Adjusted Series	spcsa
Spectrum of the Modified Irregular	spcirr
Spectrum of the RegARIMA Residuals	spcrsd
Spectrum of the Original and Seasonally Adjusted Series (Overlaid)	spcosa
Spectrum of the Indirect Modified Irregular	spciir
Spectrum of Indirect Seasonally Adjusted Series	spcisa

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4.3: Component Graphs

Component graphs allow you to select from one to four different seasonal decomposition component elements to plot. If you choose more than one, all components are graphed in reduced size on one page. See component graph formats for more information. You can scroll up to see the larger graphs of each component individually. If the selected graphs are of the same type- that is, outlier graphs, or factor graphs- then the graphs will have the same y-axis scale for easy comparisons. The keyword for component graphs is cmpnent.

Available Elements for Factor Component Graphs

Element	Element Code
Combined Holiday and TD Factors	cal
Combined Holiday and TD Factors (from X11regression)	ccal
Combined Adjustment Factors	caf
Final Adjustment Ratios	arat
Holiday Factors	hol
Indirect Adjustment Ratios	indarat
Indirect Combined Adjustment Factors	indcaf
Indirect Irregular	indirr
Indirect Seasonal Factors	indsf
Irregular	irr
Irregular Component Modified for Extremes	mirr
Irregular Modifed for Extremes from Indirect	indmirr
Prior Adjustment Factors	prior
Seasonal Factors	sf
Seasonal Factors with User-Defined Regressors	sfr
Trading Day Factors	td
Total Adjustment Factors	totadj
User-defined Regression Factors	usrdef
User-defined Seasonal Regression Factors	rgseas
X-11 Easter Factors	xeastr

Available Elements for Overlay Component Graphs

Element	Element Code
Original (or Composite) Series	ori
Calendar-Adjusted Original Series	cad
Composite Series Adjusted by Prior Factors	cmppadj
Original Data with Preliminary Adjustments	priadj
Original Series Modified for Extremes	mori
Original Series with Replaced Missing Values	mvadj
Outlier Adjusted Original (or Composite) Series	oadori
Prior Adjusted Original Series	adjori
Seasonally Adjusted Series	sa
Seasonally Adjusted Series with Annual Totals	satot
Seasonally Adjusted Series Modified for Extremes	msa
Trend	trn
Indirect Seasonal Adjustment	indsa
Indirect Seasonal Adjustment with Annual Total	indsat
Indirect Trend	indtrn
Original Modified for Extremes from Indirect	indmor
Seasonally Adjusted Series Modified for Extremes from Indirect	indmsa

Available Elements for Overlay Logs Component Graphs

Element	Element Code
Log of Original (or Composite) Series	lori
Log of Original with Replaced Missing Values	lmvadj
Log of Outlier Adjusted Original (or Composite)	loadori
Log of Prior Adjusted Original Series	ladjori
Log of Seasonally Adjusted Series	lsa
Log of Trend	ltrn

Available Elements for Outlier Component Graphs

Element	Element Code
Additive Outlier Factors	ao
Combined Outliers	otl
Level Shifts	ls
Temporary Change Outliers	tc
Indirect Additive Outlier Adjustment Factors	indao
Indirect Level Shift Adjustment Factors	indls

Available Elements for Outlier Logs Component Graphs

Element	Element Code
Log of Additive Outlier Factors	lao
Log of Combined Outliers	lotl
Log of Level Shifts	lls
Log of Temporary Change Outliers	ltc

Available Elements for Weight Component Graphs

Element	Element Code
Irregular Weights	irrwt

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4.4: Special Seasonal Factor Graphs

Three types of seasonal graphs are available: SI ratios (detrended series values) with seasonal factors by month or quarter, seasonal factors by month or quarter, and boxplots of the irregular component by month or quarter. The keyword for special seasonal factor graphs is seas.

Both SI ratio graphs and monthly seasonal factor graphs are due to Cleveland and Terpenning (1982).

SI Ratios with Seasonal Factors by Month or Quarter

When created with the element code si, the program produces as many as 16 graphs. There is one graph for each month or quarter, along with graphs with four months or quarters per page. With monthly series, there is also a graph of all 12 months on one page.

When the element code siall is used, the SI ratio plots for all twelve months or four quarters are graphed on one plot with the same scale.

Seasonal Factors by Month or Quarter

The program graphs seasonal factors by calendar month or quarter. Each calendar period has a year axis drawn at the level of its factor mean. You can graph either the seasonal factors (X-13ARIMA-SEATS's D 10 table) or the combined factors, which are the seasonal, trading day, holiday, and user-defined factors combined (X-13ARIMA-SEATS's D 16 table).

Boxplots of the Irregular Component

You can create boxplots of the irregular component by month to compare the spread of the irregular component for each month.

Available Elements for Special Seasonal Factor Graphs

Element	Element Code
SI Ratios (Graphed with Replacement Values and Seasonal Factors)	si
SI Ratios Plots on One Graph	siall
Seasonal Factors	sf
Combined Seasonal Factors	caf
Indirect Seasonal Factors	indsf
Indirect Combined Seasonal Factors	indcaf
Boxplots of the Irregular Component	irr
Boxplots of the Indirect Irregular Component	indirr

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4.5: Forecast Graphs

The program graphs the original series, the forecasts, and the confidence intervals for the forecasts. If you chose a transformation in the X-13ARIMA-SEATS run, you can choose to graph the series and forecasts on the original scale or the transformed scale. If the series does not have a transformation, you can only graph the series and the forecasts on the original scale. The keyword for the forecast graphs is forecast.

Available Elements for Forecast Graphs

Element	Element Code
Original Series and Forecasts on the Original Scale	fct
Original Series and Forecasts on the Transformed Scale	ftr

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4.6: History Graphs

You can create graphs to study the revisions for the seasonal adjustment, seasonal factors, trend, and forecasts of a series. The keyword for history graphs is history1.

You can create the following four types of history graphs:

Overlay Graphs

If you request a graph of the "Seasonal Adjustment Values", "Indirect Seasonal Adjustment Values", or "Trend Values" (elements ahst, indahst, and trhst, respectively), you will get a graph of the initial and the final estimates of that value overlaid with the original series. If you requested additional history information at certain lags when running X-13ARIMA-SEATS, the graph will also include those estimates.

Seasonal Factor Graphs

Graphs of the seasonal factor history plot the initial and the final seasonal factor estimates by calendar period. For each month or quarter, the final seasonal factors are plotted as a line and the initial seasonal factors as circles, and a year axis is drawn at the period's factor mean.

Percent Change Graphs

Three graphs are created when "Percent Changes in the Seasonal Adjustment Values" or "Percent Changes in the Trend Values" (elements csahst and ctrhst, respectively) are requested. Each graph plots two of the following for each observation: the percent change (from the previous observation) of the final estimate, the percent change of the initial estimate, and the percent change of the original series. Each is plotted as a circle or diamond, with a vertical line connecting them.

Special Trend Graphs

If you request graphs for "All Trend Revisions," "Trend Revisions for the Ending Date," or "Trend Revisions for the Ending Date," the program produces graphs that connect the estimates for trend from the lags requested when X-13ARIMA-SEATS was run. This shows the direction a trend was taking for a particular date. Each graph has a continuous line representing the final trend estimate. There is a shorter line connecting all the estimates for a particular date from the requested lags. That is, if lags 1, 2, 3, and 4 were requested, then for December 1999, the initial trend estimate is connected to the Lag 1 estimate from November, the Lag 2 estimate from October, the Lag 3 estimate from September, and the Lag 4 estimate from August to see where the trend was heading.

The graph "for the ending date" shows the trend lags only for the last date on the graph, while the graph "over the lag interval" shows trends from the end of the series back however many lags were requested, and the graph for "all trend revisions" shows the trend lags for all dates.

Concurrent Forecasts and Forecast Errors

Graphs for "Concurrent Forecasts" (element cfchst) plot the original series and the within-sample forecasts for the lags specified in the history spec. Graphs for "Concurrent Forecast Errors" (element cfehst) plot the difference between the original series and the within-sample forecasts for the specified lags.

Available Elements for History Graphs

Element	Element Code
Seasonal Adjustment Values	ahst
Indirect Seasonally Adjusted Values	indahst
Trend Values	trhst
Seasonal Factor Values	sfhst
Percent Changes in the Seasonally Adjusted Values	csahst
Percent Changes in the Trend Values	ctrhst
All Trend Revisions	trhall
Trend Revisions for the Ending Date	trhend
Trend Revisions over the Lag Interval	trhlag
Concurrent Forecasts	cfchst
Concurrent Forecast Errors	cfehst

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4.7: ACF/PACF Graphs

Graphs of the autocorrelation function and the partial autocorrelation function are available for both the residuals and for the original series, but only if the relevant spec was included when running X-13ARIMA-SEATS. Both types have the keyword acfpacf.

If you included the spec check when you ran X-13ARIMA-SEATS, you can create ACF and PACF plots of the residuals:

If you included the identify spec, you can create ACF and PACF plots from the original series. The program will create an ACF and a PACF graph for each combination of differencing and seasonal differencing that was given in the identify spec. That is, if you asked for nonseasonal differencing of 0 and 1 and seasonal differencing of 0 and 1 when you ran X-13ARIMA-SEATS, you will get eight graphs; the order of differencing is included in the subtitle:

Available Elements for ACF/PACF Graphs

Element	Element Code
ACF Plot (from Check Spec)	acf
PACF Plot (from Check Spec)	pacf
ACF of the Squared Residuals	acf2
ACF and PACF Plots (from Identity Spec)	idacf

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4.8: Outlier T-Value Graphs

Outlier T-Value Graphs allow you to compare the maximum absolute t-values from the automatic outlier procedure. There are two types of graphs you can produce; each has its own keyword.

We've been using the graphs for research into ways for finding regARIMA outliers, with only limited success. For more information, see McDonald-Johnson and Hood (2001).

Information for the Outlier T-Value graphs comes from the automatic outlier procedure from the final t-value table. By default, X-13ARIMA-SEATS only looks for additive outliers (AO) and level shifts (LS). If you ask for graphs of the temporary change (TC) outliers without requesting them specifically in X-13ARIMA-SEATS, you will get an error.

The t-value graphs will plot the maximum absolute t-values for each data point. That is, if for one particular month, say June 1989, X-13ARIMA-SEATS calculates an AO t-value of 3.1, an LS t-value of 2.2, and a TC t-value of 2.7, at June 1989 the graph shows only the AO t-value at 3.1. Another helpful feature of the maximum absolute t-value plot is that X-13ARIMA-SEATS assigns a t-value of 0 to any identified outlier. That is, if X-13ARIMA-SEATS identifies a particular month, say August 1998, as an LS, then the August 1998 LS t-value would be 0, although X-13ARIMA-SEATS would calculate valid t-values for the AO and TC effects. The greater (in absolute value) of the AO and TC t-values would appear on the graph.

If you use the keyword tvalue, the actual value of the maximum absolute t-value will be plotted, with the correct sign. If you use the keyword abtvalue, the absolute value of the maximum absolute t-value will be plotted. The first graph below was created with the keyword tvalue, and the second with the keyword abtvalue. Both keywords use the same elements.

Available Elements for T-Value Graphs

Element	Element Code
T-Values for Additive Outliers	ao
T-Values for Level Shifts	ls
T-Values for Temporary Changes	tc

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4.9: First Difference Graphs

The program graphs the first differences of the selected element by period. If the series is monthly, the differences of each month are plotted together with four months per graph; a graph of all twelve months together is also produced. The number on the graph is the last digit of the difference's year. The keyword for first difference graphs is fstdiff.

The form of the first difference graphs was developed by Stuart Scott at the Bureau of Labor Statistics where it has been used to detect outliers in the original time series. See Scott (1987) and Buszuwski and Scott (1988) for examples of using first difference graphs to identify different types of outliers.

Available Elements for First Difference Graphs

Element	Element Code
Original Series	ori
Calendar-Adjusted Original Series	cad
Original Series Adjusted by Prior Factors	priadj
Original Series Modified for Extremes	mori
Original Series with Missing Values Replaced	mvadj
Prior-Adjusted Original Series	adjori
Seasonally Adjusted Series	sa
Seasonally Adjusted Series Modified for Extremes	msa
Trend Cycle	trn
Composite Series Adjusted by Prior Factors	pacmp
Indirect Seasonally Adjusted Series	indsa
Seasonal Adjustment Modified for Extremes from Indirect	indmsa
Indirect Trend	indtrn
Original Series Modified for Extremes from Indirect	indmori

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4.10: Year-on-Year Graphs

Year-on-Year graphs plot the requested element by year in order to look for seasonal patterns in the data. The keyword for these graphs is yronyr.

The program will not create these graphs if the span is over 18 years. Use the subspan option to limit the years to be graphed.

Available Elements for Year-on-Year Graphs

Element	Element Code
Original Series	ori
Calendar-Adjusted Original Series	cad
Original Series Adjusted by Prior Factors	priadj
Original Series Modified for Extremes	mori
Original Series with Missing Values Replaced	mvadj
Prior-Adjusted Original Series	adjori
Seasonally Adjusted Series	sa
Seasonally Adjusted Series Modified for Extremes	msa
Trend Cycle	trn
Composite Series Adjusted by Prior Factors	pacmp
Indirect Seasonally Adjusted Series	indsa
Seasonal Adjustment Modified for Extremes from Indirect	indmsa
Indirect Trend	indtrn
Original Series Modified for Extremes from Indirect	indmori

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4.11: Sliding Spans Graphs

The sliding spans diagnostic creates up to four overlapping subspans of your data, seasonally adjusts each subspan, and compares the resulting seasonally adjusted values. To create graphs for this diagnostic, use the keyword sspans.

You can create four types of sliding spans graphs. The first is an overlay graph of the seasonal factors of each span; if the percent difference between the largest and smallest value is greater than the cutoff value, usually 3, this graph will also show dots indicating the maximum and minimum value.

You can also create a graph of these maximum percent differences chronologically, by year, or by month or quarter. In each case, a horizontal line showing the cutoff value will also be graphed.

These four graphs can be created for the seasonal factors (or seasonally adjusted value, depending on your transformation type), the month-to-month or quarter-to-quarter percent changes of the seasonally adjusted series, the indirect seasonal factors, and the indirect month-to-month or quarter-to-quarter percent changes.

Available Elements for Sliding Spans Graphs

Element	Element Code
Seasonal Factors of Spans	sfspan
Maximum Percent Difference (MPD) of Seasonal Factors	sfmpd
MPD of Seasonal Factors by Year	sfmpdy
MPD of Seasonal Factors by Period	sfmpdp
Period-to-Period Seasonal Adjustment Changes of Spans	chspan
MPD of Period-to-Period Changes	chmpd
MPD of Period-to-Period Changes by Year	chmpdy
MPD of Period-to-Period Changes by Period	chmpdp
Indirect Seasonal Factors of Spans	isfspan
MPD of Indirect Seasonal Factors	isfmpd
MPD of Indirect Seasonal Factors by Year	isfmpdy
MPD of Indirect Seasonal Factors by Period	isfmpdp
Indirect Period-to-Period Seasonal Adjustment Changes of Spans	ichspan
MPD of Indirect Period-to-Period Changes	ichmpd
MPD of Indirect Period-to-Period Changes by Year	ichmpdy
MPD of Indirect Period-to-Period Changes by Period	ichmpdp

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4.12: SEATS Filter and Diagnostic Graphs

Four types of graphs using two keywords can be created for SEATS adjustments. Note that to create these graphs, X-13 must be run with out=0 or out=2 in the seats spec.

To graph filters used in SEATS adjustments and their time shifts and squared gains, use the keyword filter. You can list up to four elements on each line of the graph list file (.gls) for these filter graphs. Each filter will be plotted in its own graph; however, all the requested time shift graphs found on one line will be plotted together, as will all requested squared gain graphs.

Available Elements for SEATS Filter Graphs

Element	Element Code
Concurrent Seasonal Adjustment Filter	fltsac
Concurrent Trend Filter	flttrnc
Symmetric Seasonal Adjustment Filter	fltsaf
Symmetric Trend Filter	flttrnf
Time Shift of Concurrent Seasonal Adjustment Filter	tssac
Time Shift of Concurrent Trend Filter	tstrnc
Squared Gain of Concurrent Seasonal Adjustment Filter	sgsac
Squared Gain of Concurrent Trend Filter	sgtrnc
Squared Gain of Symmetric Seasonal Adjustment Filter	sgsaf
Squared Gain of Symmetric Trend Filter	sgtrnf

SEATS diagnostic graphs can be graphed using the keyword seats. These show the fully differenced SEATS seasonal adjustment or SEATS trend, and the seasonal period length sums of the SEATS seasonal factors. See the X-13ARIMA-SEATS manual (U.S. Census Bureau, 2012) for more information.

Available Elements for SEATS Diagnostic Graphs

Element	Element Code
Fully Differenced SEATS Seasonal Adjustment	seatdsa
Fully Differenced SEATS Trend	seatdtr
Seasonal Period Length Sums of the SEATS Seasonal Factors	seatssm

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4.13: Power Graphs

Power graphs are plots of the original series with a Box-Cox power transformation applied. The keyword for these graphs is power. The elements for these graphs is the Box-Cox power lambda λ. Setting lambda λ = 1 will produce a graph of the original series; lambda λ = 0 produces a graph of the logged series.

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4.14: Overlay Graphs for Comparing Two Series

Overlay graphs of two series can be produced to compare the adjustments. The keyword for these graphs is overlay2.

These overlay graphs need two different models to compare. Enter the names of the graphics metafiles for the two models on the same line in the graphics metafile list file (the .mls file). An example is given in the examples below.

Up to three elements can be chosen for each series. The elements do not have to be the same for each series. In the graphics list file (the .gls file), list the elements for the first series after the colon after overlay2. If the elements for the second series are the same as those for the first series, you do not need to enter anything else. If different elements are required for the second series, put another colon on the same line, and list the elements for the second series. So, to create a graph with the original series and the seasonally adjusted series of the first model and the seasonally adjusted series for the second series, put the line

overlay2: ori sa: sa

in the .gls file.

The elements available for these graphs match those for overlay graphs.

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4.15: Component Graphs for Comparing Two Series

You can compare the components of two different adjustments using the keyword cmpnent2.

When you request a component graph to compare two series, the program creates two graphs: the plots of the component for each series on one page, and either the difference or the ratio between the values of that component for each series. The ratio is graphed when the element is either a factor or the irregular and the adjustment is multiplicative, and the difference is graphed otherwise.

As two models are being compared, the two series must both be named on the same line in the graphics metafile list (the .mls file). An example of this is in the examples below.

The elements available for these graphs are the same as those for component graphs.

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4.16: History Graphs for Comparing Two Adjustments

History graphs allow you to compare two models by looking at the AIC Differences History and the Sum of Squared Forecast Error Differences History. For the Sum of Squared Forecast Error Differences graph, the program superimposes all available forecast lags on a single graph. The keyword for history graphs is history2.

These history graphs are discussed in Findley, Monsell, Bell, Otto and Chen (1998) and are related to diagnostics presented in Findley (1990, 1991).

You can also create graphs of the Percent Changes in the Seasonally Adjusted Series or the Trend. Two graphs are created when these elements are requested. One plots the month-to-month change of the concurrent adjustment for both series, connected by a vertical line to highlight the difference. The second does the same for the final adjustment.

History graphs require graphics output from two different models to compare. You must enter the names of the graphics metafiles for the two different models for the history graph on the same line in the graphics metafile list file. An example graphics metafile list file (.mls) is given in the examples below.

Available Elements for History Graphs

Element	Element Code
AIC	aichst
Sum of Squared Forecast Errors	fcthst
Percent Change in the Seasonally Adjusted Series	csahst
Percent Change in the Trend	ctrhst

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4.17: SI Ratios for Comparing Two Adjustments

These graphs allow you to compare two models by graphing the SI ratios (the detrended series), the SI ratios with the extreme values replaced, or the SI ratios with the replaced value and the original value. To compare two adjustments, the names of both models must appear on the same line in the graphics metafile list file (.mls); see the Example 3 in Section 5 below. The keyword for these graphs is rsi2.

Available Elements for SI Ratio Graphs

Element	Element Code
SI Ratios	si
RSI Ratios	rsi
RSI Ratios with Original Value	sirsi

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4.18: Forecast Graphs for Comparing Two Adjustments

You can compare the forecasts of two models using the keyword fcast2.

To compare two models, the names of each must be on the same line of the graphics metafile list file (.mls); see Example 3 in Section 5 below.

Available Elements for Forecast Comparison Graphs

Element	Element Code
Original Series and Forecasts on Original Scale	fct
Original Series and Forecasts on Transformed Scale	ftr

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4.19: Spectrum Graphs for Comparing Two Adjustments

You can compare the spectrum plots of two models using the keyword spect2.

In order to compare two adjustments, the names of both models must be on the same line of the graphics metafile list file (.mls). See Example 3 in Section 5.

Available Elements for Spectrum Comparison Graphs

Element	Element Code
Spectrum of the Original Series	spcori
Spectrum of the Seasonally Adjusted Series	spcsa
Spectrum of the Irregular	spcirr
Spectrum of the RegARIMA Residuals	spcrsd
Spectrum of the Indirect Modified Irregular	spciir
Spectrum of Indirect Seasonally Adjusted Series	spcisa

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4.20: Seasonal Factor by Month Graphs for Comparing Two Adjustments

Use the keyword seas2 to plot the seasonal factors by month for two adjustments on one graph.

Since these graphs compare two adjustments, the names of both models must appear on the same line in the graphics metafile list file (.mls); see Example 3 in Section 5 for an example.

To overlay the seasonal factors, combined adjustment factors, indirect seasonal factors, or indirect combined adjustment factors of both models, the graph list file can just list the required element. However, if you'd like to overlay one type of seasonal factor from the first model with another type of seasonal factor for the second model, you must put the keyword, a colon, the first model's element type, a second colon, and then the second model's element type. For example,

seas2: sf: indsf

will graph the seasonal factors of model one with the indirect seasonal factors of model two. Note that if model one and model two are the same (that is, you list the same series twice on one line in the .mls file), this will create an overlay graph of the direct and indirect seasonal factors for an adjustment.

Available Elements for Seasonal Factor Comparison Graphs

Element	Element Code
Seasonal Factors	sf
Combined Adjustment Factors	caf
Indirect Seasonal Factors	indsf
Indirect Combined Adjustment Factors	indcaf

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5: Examples

These examples use data from one-family housing starts in the four U.S. geographic regions (Northeast, South, Midwest, and West), as well as the U.S. total one family housing starts. The X-13ARIMA-SEATS spec files are called ne1.spc, mw1.spc, so1.spc, and we1.spc, with tot1F.spc containing the composite spec to create the U.S. total. To run this series, a metafile is needed. The contents of this file, called starts.mta, are:

ne1
mw1
so1
we1
tot1F

Before creating any graphs, X-13ARIMA-SEATS must run this metafile in graphics mode. To do this, enter x13a -m starts -g c:\x13a\graphics in DOS. The -m option informs the program that this is a metafile, the -g option instructs X-13ARIMA-SEATS to produce the graphics output files needed, and the directory after the -g is the destination for the output files.

After the graphics output files have been produced, you are ready to run the X-13-Graph Batch program.

Example 1

Goal: To learn to set up the files needed to run the X-13-Graph Batch program.

Suppose you wish to compare the original series with the seasonally adjusted series for all four regions and for the total, and the original series with the outlier-adjusted series in the case of those series with outliers.

The first step is to create the .mls and .gls files. These must have the same name; use the name starts. As you want graphs for all five series, the starts.mls file is

ne1
mw1
so1
we1
tot1F

Note that this looks just like the metafile used to run X-13ARIMA-SEATS. The starts.gls file is

overlay: ori sa
overlay: ori indsa
overlay: ori oadori

The first command produces the graph of the original series and the seasonally adjusted series superimposed. The second overlay statement compares the original series with the seasonally adjusted series from the indirect adjustment. As this element exists only for the composite series, tot1F, X-13-Graph produces this graph only for that one series. The third command creates a graph of the original series and the outlier-adjusted series. The series for the South and for the composite have no outliers, so overlay graphs from the third statement are not created for these series.

Next, in x13gbat.sas, set the value of the variable inptfile equal to starts and the value of inptdir equal to the directory specified after the -g option when X-13ARIMA-SEATS was run. Submit the program by pressing the submit button (the running man), or by selecting submit from the Run pull down menu.

Once the program has run, there will be nine graphs. Examples of them follow:

This is the graph of the original and the seasonally adjusted series of the Northeast data. Similar graphs exist for the other three regions and for the U.S. total.

This graph is the original series for the U.S. totals, along with the seasonally adjusted series from the indirect adjustment. It is the only graph produced from the overlay: ori indsa statement in the .gls file.

This is one of three graphs of original series and the outlier-adjusted original series; this one is from the Northeast. Most of the differences seem to be between 1985 and 1991. In the next example, this portion of the series will be expanded to better see these differences.

Example 2

Goal: To use the color, line width, and subspan global options in creating graphs. Also, to learn to modify the .gls and .mls files without deleting content.

In this example, you will modify a graph plotted in the previous example in order to better see some of its details, and also create a component graph of this region's additive outliers.

First, modify the starts.gls file, keeping only one of the overlay graphs adding a component graph, so that the graph list file looks like:

overlay: ori oadori
cmpnent: ao

Next, modify the graphics metafile list, since the only series to be graphed is the Northeast region. One way to do this is to delete the series that aren't being graphed, but as you may want to create more graphs from them later, you can comment them out instead by putting a # sign in front of them. Starts.mls will look like:

ne1
#mw1
#so1
#we1
#tot1F

In order to graph only part of a series, use the subspan option. In the x13gbat.sas program, change substart to 1985.Jan, and subend to 1991.Dec. Graphs of the outlier-adjusted series place a dot where each additive outlier is (and a reference line where the level shifts and temporary changes are). To better see this dot, you can change the line widths of the first and second line to 1 by letting lw1 and lw2 equal 1. If you also want to change the default colors of the graph, you can change the appropriate color variables. Changing color1 to purple and color2 to orange creates the following two graphs after the program is run:

Note that in the overlay graph, the original series, which was listed first in the .gls file, takes the color assigned to color1, and the outlier adjusted series, which was listed second, takes the color2 value. The second graph has only one element, so it takes the color given in color1.

Example 3

Goal: To create graphs to compare two series, and to modify them using the color, line type, line width, y-divisor, gridline, and subtitle global options.

If you want to compare the seasonally adjusted series for two different series, you can use the overlay graphs for two models or the component graphs for two series. The overlay graph will create a plot with the seasonally adjusted series of each model overlaid on one graph; the component graph will create a graph with each seasonally adjusted series on its own plot, and will also create a graph of the differences between the two series.

To create graphs to compare two series, the names of the series must be on the same line in the graphics metafile list (.mls) file. To compare the housing starts from the Midwest to those from the Northeast, the .mls file must read:

mw1 ne1

The graph list file (.gls) must read

overlay2: sa: sa
cmpnent2: sa

in order to create graphs for the seasonally adjusted series for each model. Actually, since the same elements are being plotted for the first and the second series in the overlay graph, the second colon and sa are not needed in the overlay2 command, but including them does no harm.

The following three graphs are produced when the program is run using the default options:

You can modify the appearance of the overlay graph with some of the global options. In the x13gbat.sas program, locate and change the following variables:

%let color1=gray;
%let color2=cyan;
%let ltype1=1;
%let ltype2=1;
%let lw1=1;
%let lw2=1;
%let subtitle=Midwest;
%let subtitle2=Northeast Housing Starts;
%let ydivisor=1000;
%let gridlinemo=12;

The variables color1 and color2 will change the first graph to gray and the second to cyan; ltype1 and ltype2 will make the plots of both series be an unbroken line, while lw1 and lw2 make both graph lines thinner. The subtitle of the overlay graphs for two series is the title of the first, the word 'and', and then the title of the second; the default subtitle is then 'MIDWEST ONE FAMILY Housing Starts and NORTHEAST ONE FAMILY Housing Starts.' Changing subtitle and subtitle2 will create the subtitle 'Midwest and Northeast One Family Housing Starts.' Note that the graph of the seasonally adjusted series has a y-axis ranging from 0 to 30000. Including a ydivisor of 1000 will change the axis range to 0 to 30, and will include the label 'In Thousands.' This option is very useful when the y-axis is in the range of millions or billions. Finally, changing gridlinemo to 12 will move the default gridlines from January to December to highlight the last month of the year instead of the first. The color and line type of these gridlines can be customized using the colorg and ltypeg variables, if desired.

Running the program with these options creates the following graph:

Note: If you wish to keep the default values for the variables handy while temporarily changing them, you can insert the new value after the equal sign, type a semicolon, and then insert a star (*) before the original value, as such:

%let ltype1 = 1;
%let ltype2 = 1;*21;

SAS views everything between a star and a semicolon as a comment, so the *21; will be ignored while the program is running.

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6: Reporting Problems

Please report all problems or provide any feedback to Demetra Lytras by email (demetra.p.lytras@census.gov) or to Kathy McDonald-Johnson either by email (x12@census.gov) or by telephone at (301) 763-7602.

If the program graphs something incorrectly (including titles and legends), or doesn't produce a graph at all, please report the problem as soon as possible.

To help us diagnose the problem, it is helpful if we have

1. the X-13ARIMA-SEATS data file,
2. the X-13ARIMA-SEATS .spc file,
3. the .mls, .gmt and .gls files, and
4. a copy of the SAS Log from that X-13-Graph run.

The SAS Log will be in the file x13GbatLog.sas, located in the directory in which the program is installed, typically c:\x13graph\appl.

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7: Acknowledgements

Brian Monsell wrote the basic SAS code for reading in the X-13ARIMA-SEATS files and for the SI ratio graphs. David Findley and Brian Monsell provided valuable suggestions for the design of the graphs and the documentation. Kellie C. Wills wrote the SAS code for many of the graphs. Many thanks to everyone who gave us suggestions.

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8: References

Buszuwski, J.S. and S. Scott (1988), "On the Use of Intervention Analysis in Seasonal Adjustment," Proceedings of the Business and Economic Statistics Section, American Statistical Association, Alexandria, VA, 337-342.

Cleveland, W.S. and I. Terpenning (1982), "Graphical Methods for Seasonal Adjustment," Journal of the American Statistical Association , 77, 52-72.

Findley, D.F. (1990), "Making Difficult Model Comparisons Graphically," Proceedings of the Section on Survey Research Methods, American Statistical Association, Alexandria, VA.

Findley, D.F. (1991), "Model Selection for Multi-Step-Ahead Forecasting," Proceedings of the Business and Economic Statistics Section, American Statistical Association , Alexandria, VA.

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