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
- 3: Instructions for Running X-13-Graph in Batch Mode
- 3.1: Running X-13ARIMA-SEATS in Graphics Mode
- 3.2: Additional Files Needed
- 3.3: 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

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.

**Licensing information for this software
can be found at http://www.census.gov/srd/www/disclaimer.html**.

Return to contents.

X-13-Graph Batch is a SAS^{Â®} program using SAS/GRAPH^{Â®} (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.

Return to contents.

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

- Create a directory for the program;
**c:\x13graph**is recommended, and will be used throughout this document. - Copy the file
**x13gbat.zip**to the**c:\x13graph**directory. - Double Click on
**x13gbat.zip**in Windows^{Â®}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. ^{Â®} indicates USA
registration.

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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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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.

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 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.

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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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:

- Open the SAS system on your operating system.
(For example, in Windows, double-click on the SAS icon.)
- 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. - 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.- 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. - 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:

- 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. - 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.

- Go to the command line. This is the text entry area on the tool bar,
usually at the left side.
Enter the command
- 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 ;** - 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.

- 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.

- SAS Libname
- 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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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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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.

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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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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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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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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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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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.

Return to contents.

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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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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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.

Return to contents.

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.

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.

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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Graphs of 10 times the log_{10}
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.

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 |

Return to contents.

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**.

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 |

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 |

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 |

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 |

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 |

Element | Element Code |
---|---|

Irregular Weights | irrwt |

Return to contents.

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.

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 |

Return to contents.

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**.

Element | Element Code |
---|---|

Original Series and Forecasts on the Original Scale | fct |

Original Series and Forecasts on the Transformed Scale | ftr |

Return to contents.

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.

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 |

Return to contents.

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:

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 |

Return to contents.

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.

Element | Element Code |
---|---|

T-Values for Additive Outliers | ao |

T-Values for Level Shifts | ls |

T-Values for Temporary Changes | tc |

Return to contents.

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.

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 |

Return to contents.

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.

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 |

Return to contents.

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.

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 |

Return to contents.

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.

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.

Element | Element Code |
---|---|

Fully Differenced SEATS Seasonal Adjustment | seatdsa |

Fully Differenced SEATS Trend | seatdtr |

Seasonal Period Length Sums of the SEATS Seasonal Factors | seatssm |

Return to contents.

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.

Return to contents.

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.

Return to contents.

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.

Return to contents.

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.

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 |

Return to contents.

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**.

Element | Element Code |
---|---|

SI Ratios | si |

RSI Ratios | rsi |

RSI Ratios with Original Value | sirsi |

Return to contents.

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.

Element | Element Code |
---|---|

Original Series and Forecasts on Original Scale | fct |

Original Series and Forecasts on Transformed Scale | ftr |

Return to contents.

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.

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 |

Return to contents.

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.

Element | Element Code |
---|---|

Seasonal Factors | sf |

Combined Adjustment Factors | caf |

Indirect Seasonal Factors | indsf |

Indirect Combined Adjustment Factors | indcaf |

Return to contents.

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.

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.

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**.

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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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

- the X-13ARIMA-SEATS data file,
- the X-13ARIMA-SEATS .spc file,
- the .mls, .gmt and .gls files, and
- 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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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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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.

Findley, D.F., B.C. Monsell, W.R. Bell, M.C. Otto and B.-C. Chen (1998).
"New Capabilities and Methods of the X-13ARIMA-SEATS Seasonal Adjustment Program,"
*Journal of Business and Economic Statistics* , 16, 127-177 (with discussion).

McDonald-Johnson, K. and C.C. Hood (2001),
"Outlier Selection for RegARIMA Models," to appear in the *Proceedings
of the Business and Economic Statistics Section, American Statistical
Association*, Alexandria, VA.

SAS Institute, Inc. (1990), *SAS/GRAPHÂ®*
*Software: Reference, Version 6, First Edition, Volumes 1 and 2*,
Cary,
NC: SAS Institute, Inc.

Scott,S. (1987), "On the Impact of Outliers on Seasonal Adjustment,"
*Proceedings of the Business and Economic Statistics Section,
American Statistical Association*, Alexandria, VA, 469-474.

U.S. Census Bureau (2012),
*X-13ARIMA-SEATS Reference Manual*, Washington, DC.

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Source: U.S. Census Bureau | OSMREP and CSRM | (301) 763-1649 (or x12@census.gov) |
Last Revised:
December 18, 2013