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PROBPLOT Statement |
See CAPPROB3 in the SAS/QC Sample Library |
When you request a lognormal probability plot,
you must specify
the shape parameter for the lognormal distribution
(see Table 9.13 for the equation).
The value of
must be positive, and
typical values of
range from 0.1 to 1.0.
Alternatively, you can specify that
is to be
estimated from the data.
The following statements illustrate the first approach by creating a series of three lognormal probability plots for the variable DIAMETER introduced in the preceding example:
title 'Lognormal Probability Plot for Diameters'; proc capability data=measures noprint; probplot diameter / lognormal(sigma=0.2 0.5 0.8 color=yellow) HREF=95 lHREF=1 square cHREF=red cframe = ligr; run;
The LOGNORMAL option requests plots based on the lognormal
family of distributions, and the
SIGMA= option requests plots for equal to
0.2, 0.5, and 0.8.
These plots are displayed in
Figure 9.3,
Figure 9.4,
and
Figure 9.5, respectively.
The value
in Figure 9.4
produces the most linear pattern.
The SQUARE option displays the probability plot in a square format, the HREF=option requests a reference line at the 95 th percentile, and the LHREF=option specifies the line type for the reference line.
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Based on Figure 9.4, the 95 th percentile of the diameter distribution is approximately 5.9 mm, since this is the value corresponding to the intersection of the point pattern with the reference line.
The following statements illustrate how you can
create a lognormal probability plot for DIAMETER
using a local maximum likelihood estimate for .
title 'Lognormal Probability Plot for Diameters'; proc capability data=measures noprint; probplot diameter / lognormal(sigma=est color=yellow) HREF=95 lHREF=1 square cHREF=red cframe = ligr; run;
The plot is displayed in
Figure 9.6.
Note that the maximum likelihood estimate of
(in this case 0.041)
does not necessarily produce the most linear point
pattern.
This example is continued in
Example 9.2.
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