You can use the SGPLOT
and SGPANEL procedures to produce fit plots and ellipses (the ellipses
plot is available with the SGPLOT procedure only). Fit plots represent
the line of best fit (trend line) with confidence limits.
The plot statements
include many options for controlling how the output is displayed.
The options that are available depend on the plot type. However, some
general options apply to most of the fit and confidence plots. For
example, options enable you to do the following:
add confidence limits (CLM) to
the plot. When you add CLM limits, you can specify the confidence
level, the transparency for the confidence limits, and other visual
attributes. You can add CLM limits to loess, penalized B-spline, and
add prediction limits (CLI) for
the individual predicted values. When you add CLI limits, you can
specify the text that appears for the limits and other visual attributes.
You can add CLI limits to penalized B-spline and regression plots.
control the appearance of the markers
and the fit line. You can also specify a smoothing parameter.
add and customize curve and data
specify legend labels. You can
also show or hide the legend entries for the CLM limits, the CLI limits,
and the fit line.
group the data by the values of
a variable. A separate plot is created for each unique value of the
grouping variable. The plot elements for each group value are automatically
distinguished by different visual attributes.
specify the value of an ID variable
in an attribute map data set. You specify this option only if you
are using an attribute map to control visual attributes of the graph.
Not all of these features
are available for all of the plots. Also, the list does not include
all available options.
fit and confidence plots are described in the following sections. If you run the examples, your output might differ somewhat
depending on the size of your graphics. The examples here were specified
to be a particular size using the following statement:
ods graphics on / width=4in;