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Modeling and Multivariate Methods - SAS

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626 Visualizing, Optimizing, <strong>and</strong> Simulating Response Surfaces Chapter 24<br />

Statistical Details<br />

Table 24.5 Strata Intervals (Continued)<br />

Strata Number Inside Distance Outside Distance<br />

2<br />

i<br />

d + 2d<br />

d + 2 2d<br />

d + ( i–<br />

1) 2d d+<br />

i 2d<br />

N Strata – 1<br />

previous<br />

∞<br />

The default number of strata is 12. To change the number of strata, a hidden comm<strong>and</strong> N Strata is available<br />

if you hold the Shift key down while clicking on the red triangle next to Simulator.<br />

Figure 24.79 Showing the N Strata Menu Option<br />

Increase the sample size as needed to maintain an even number of strata.<br />

For each simulation run,<br />

1. Select a strata as mod(i – 1, N Strata ) for run i.<br />

2. Determine a r<strong>and</strong>om n-dimensional direction by scaling multivariate Normal (0,1) deviates to unit<br />

norm.<br />

3. Determine a r<strong>and</strong>om distance using a chi-square quantile appropriate for the strata of a r<strong>and</strong>om uniform<br />

argument.<br />

4. Scale the variates so the norm is the r<strong>and</strong>om distance.<br />

5. Scale <strong>and</strong> re-center the variates individually to be as specified for each factor.<br />

The resulting factor distributions are multivariate normal with the appropriate means <strong>and</strong> st<strong>and</strong>ard<br />

deviations when estimated with the right weights. Note that you cannot use the Distribution st<strong>and</strong>ard<br />

deviation with weights, because it does not estimate the desired value. However, multiplying the weight by a<br />

large value, like 10 12 , <strong>and</strong> using that as a Freq value results in the correct st<strong>and</strong>ard deviation.

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