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Opposite to augment DOE, hou could I quickly determine the DOE I need to remove to maximize the D-efficiency of resting DOE?
Hi Pals,
I have collected 30 historical DOE which is not orthogonal at all. On JMP 17, the resulted D-efficiency is only 32 so I want to remove the most 1~3 nonorthogonal DOE before I augment any DOE. Is there any quick way to do that? Thanks! Currently, I can only manually recoginize the most nonorthogonal DOE from scatterplot matrix based on the design uniformity and re-calcuate the D-efficiency after remove it.
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Re: Opposite to augment DOE, hou could I quickly determine the DOE I need to remove to maximize the D-efficiency of resting DOE?
Hi @Fruit325,
One option could be to store all the runs in a data table and use them as candidate runs in the platform Custom Design to select the most informative runs with a D-Optimality criterion.
See https://www.jmp.com/support/help/en/17.2/#page/jmp/factors.shtml
Hope this option may help you,
One option could be to store all the runs in a data table and use them as candidate runs in the platform Custom Design to select the most informative runs with a D-Optimality criterion.
See https://www.jmp.com/support/help/en/17.2/#page/jmp/factors.shtml
Hope this option may help you,
Victor GUILLER
"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)
"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)
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Re: Opposite to augment DOE, hou could I quickly determine the DOE I need to remove to maximize the D-efficiency of resting DOE?
Hi @Fruit325,
One option could be to store all the runs in a data table and use them as candidate runs in the platform Custom Design to select the most informative runs with a D-Optimality criterion.
See https://www.jmp.com/support/help/en/17.2/#page/jmp/factors.shtml
Hope this option may help you,
One option could be to store all the runs in a data table and use them as candidate runs in the platform Custom Design to select the most informative runs with a D-Optimality criterion.
See https://www.jmp.com/support/help/en/17.2/#page/jmp/factors.shtml
Hope this option may help you,
Victor GUILLER
"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)
"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)
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Re: Opposite to augment DOE, hou could I quickly determine the DOE I need to remove to maximize the D-efficiency of resting DOE?
I agree with @Victor_G . That is how you should do it.
It depends on the nature of the data, of course, but removing 1 to 3 observations might not make a big difference to the D-efficiency. You may also need to think about augmenting with new runs to get a more useful data set.
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