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PYS
PYS
Level II

linear constraints in simulator

Hello,

I performed a DoE with three continuous factors selected as significant.

This DoE contains a linear constraint between two of them (temperature and time) since we already knew that the chemical reaction investigated didn't happen at low temperature and short times.

My questions is about the simulator. When I fitted the model and wanted to simulate the responses with the MC simulator, there are simulations in conditions outside my experimental domain (the whole experimental domain has been simulated without considering the linear constrain).

Is it possible to take into account the linear constraint in the simulator or at least when plotting the simulated results?

 

Thanks for your time

2 ACCEPTED SOLUTIONS

Accepted Solutions

Re: linear constraints in simulator

The functionality for the profiler simulator to observe linear constraints was added in JMP 17.  For versions of JMP before version 17, a possible workaround is to use the "Output Random Table" option.  It should output uniformly distributed random points that observe the linear constraints and the predictions.

View solution in original post

PYS
PYS
Level II

Re: linear constraints in simulator

Thank you for the reply.

Since I use JMP pro v15, I don't have access to the new tools.

Finally, I used the simulator over the whole experimental range end filtered out the predictions that didn't meet my constraints for plotting.

View solution in original post

2 REPLIES 2

Re: linear constraints in simulator

The functionality for the profiler simulator to observe linear constraints was added in JMP 17.  For versions of JMP before version 17, a possible workaround is to use the "Output Random Table" option.  It should output uniformly distributed random points that observe the linear constraints and the predictions.

PYS
PYS
Level II

Re: linear constraints in simulator

Thank you for the reply.

Since I use JMP pro v15, I don't have access to the new tools.

Finally, I used the simulator over the whole experimental range end filtered out the predictions that didn't meet my constraints for plotting.