Hi,
I Designed a set of experiments using Latin Hypercube Design (3 Factors), ran all the simulations (CFD simulations), and now I am analyzing the responses using Gaussian Process.
What does mean each term in the table named Model Report?
I believe that larger numbers (for example in the main effect column) mean that the factor has a more important effect on the response. Is that right? For example, in this figure, the more important factor would be the wind direction, and the effect of separation distance does not affect significantly the response. Is this interpretation alright?
How should I interpret the theta and total sensitivity columns?
I would like the analysis method not only to give me the correlation equation (model), but also a kind of screening, pointing to the most relevant factors in the problem. Is there any other analysis that may be better for this than Gaussian Process?
How should I analyze if the model fits well the results when using the Gaussian process, is there a criterion or rule of thumb that I should follow?
I'm new using JMP and Gaussian Process, so forgive me if my questions are too basic.
