Note: See One-sided Cusum Chart in the SAS/QC Sample Library.
This example is a continuation of the previous example that illustrates how to save cusum scheme parameters in a data set specified with the OUTLIMITS= option. This enables you to apply the parameters to future data or to subsequently modify the parameters with a DATA step program.
ods graphics on; title 'One-Sided Cusum Analysis'; proc cusum data=Cans; xchart Weight*Hour / mu0 = 8.100 /* target mean for process */ sigma0 = 0.050 /* known standard deviation */ delta = 1 /* shift to be detected */ h = 3 /* cusum parameter h */ k = 0.5 /* cusum parameter k */ scheme = onesided /* one-sided decision interval */ outlimits = cusparm odstitle = title markers; label Weight = 'Cusum of Weight'; run;
The chart, shown in Figure 6.10, is similar to the one in Figure 6.6 but is created by using ODS Graphics because the ODS GRAPHICS ON statement is specified before the PROC CUSUM statement.
The OUTLIMITS= data set is listed in Figure 6.11.
Figure 6.11: Listing of the OUTLIMITS= Data Set cusparm
One-Sided Cusum Analysis |
Obs | _VAR_ | _SUBGRP_ | _TYPE_ | _LIMITN_ | _H_ | _K_ | _SCHEME_ | _MU0_ | _DELTA_ | _MEAN_ | _STDDEV_ | _ARLIN_ | _ARLOUT_ |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Weight | Hour | STANDARD | 1 | 3 | 0.5 | ONESIDED | 8.1 | 1 | 8.09747 | 0.05 | 117.596 | 6.40391 |
The data set contains one observation with the parameters for process Weight
. The variables _TYPE_
, _H_
, _K_
, _MU0_
, _DELTA_
, and _STDDEV_
save the parameters specified with the options SCHEME=, H=, K=, MU0=, DELTA=, and SIGMA0=, respectively. The variable _MEAN_
saves an estimate of the process mean, and the variable _LIMITN_
saves the nominal sample size. The variables _ARLIN_
and _ARLOUT_
save the average run lengths for and for .
The variables _VAR_
and _SUBGRP_
save the process and subgroup-variable. The variable _TYPE_
is a bookkeeping variable that indicates whether the value of _STDDEV_
is an estimate or a standard value.
For more information, see OUTLIMITS= Data Set.