Hello, I'm trying to make a design for a nonlinear model. Some prior knowledge of the parameters is available: a guess for the mean of the parameters as well as a guess for the variance-covariance matrix. I've used the mean to initialise the model, but I'm not sure on how to use the variance-covariance matrix. On the following picture you can see the option to fill in values for the parameters: http://www.jmp.com/support/help/Creating_a_Nonlinear_Design.shtml#85515 What happens if I fill in 95% confidence intervals for all my parameters? If I put number of radii to zero in advanced options (local optimal design) will these parameter values still somehow be used? I have strong correlations between parameters in my prior distribution. Is there a way JMP can (or does) take this into account? Thanks,

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