JMP Wish List

What inspired this wish list request?  The need to compare the model built from a DOE ran in a simulation software with the model from the exact same DOE ran in an experiment in the lab.    What is the improvement you would like to see?  Overlay in the profiler if two different models in the same row. For more detail please look at the post below https://community.jmp.com/t5/Discussions/Overlay-profiler-from-two-different-models/m-p/708222#M89253   Why is this idea important?  It helps to see the mismatch between the simulation and the experimental DOE results and helps calibrate the simulation software model better and design better DOEs in the next experiments.   ... View more

What inspired this wish list request?  Need to vizualize in a ternary plot big amounts of mixture data generated from Monte Carlo simulation     What is the improvement you would like to see?  Need in ternary graph same density contour plots as already implemented for other types of graphes    Why is this idea important?  This would greatly improve the vizualization of big data for mixture application     ... View more

What inspired this wish list request?    In chemical industry, it is very common to optimize formulation which results from the selection of raw materials, the ratios in which to blend them and the process conditions used to manufacture them. For example, to optimize a synthesis, you want to choose the reactants, the solvant, the catalyst among a list of possible molecule, to optimize their ratio, and process variable such as temperature, time, mixing power, ...       What is the improvement you would like to see?    Using custom design, it is difficult (but not impossible) to deal with this problematic. For example, you want that the model does not depend on the catalyst molecule when the amount of catalyst is null. To deal with it, we need to use some tricks such as the one describe here : https://community.jmp.com/t5/Discussions/How-do-I-indicate-that-a-mixture-factor-can-take-a-number-of/m-p/387460#M63775     Several approach exists in the litterature : - Muteki, K., MacGregor, J.F., Ueda, T., 2007. Mixture designs and models for the simultaneous selection of ingredients and their ratios. Chemometrics and Intelligent Laboratory Systems. - Hada, S., n.d. Product and Mixture Design in Latent Variable Space by Chemometric Techniques. It would be very interesting to have a plateform in JMP that can implement this kind of DoE.     Why is this idea important?    This is very important to speed up the formulation of many products such as tire, shampoo, polymers, flame retardant, and so on... In our company, this kind of DoE represent a least one third of the DoE. ... View more

What inspired this wish list request?  Often times a split plot design cannot be completed in a single experimental session.  Multiple sessions over multiple days are required (examples:  firing of a ceramic, melt tanks, acid baths, or other hard to change factors with time and cost change-overs).   What is the improvement you would like to see?  Consider adding an option for blocking (Days or other periods, batches of raw material...) for split plot design when factors in the design are identified as hard-to-change. why is this idea important?  Ease of use.  Blocking of a split plot can be done but is not intuitive; requires one to know how to manipulate/trick the software by using a categorical factor and doing some manipulation of the resulting design.  Current version of jmp is 17.1     ... View more

What inspired this wish list request? Trying to augment and existing design that was built from a candidate file (due to design constraints) and finding that the augmentation can't use candidate points for run selection     What is the improvement you would like to see? Add use of Candidate files into the Augment Design Platform.      Why is this idea important? Allows augmented design to fit the custom constraints set out by a candidate file as constraints are unchanged from original design     ... View more

I don't have a lot of faith in the 'plot residuals by normal quantiles' for doing model diagnostics. I have typically saved the residuals from the model to a new column, then used the Distribution platform to create a normal quantile plot there.   The fit of the solid red line does not seem to match up well with where the residuals fall using Fit Least Squares. The slope of the solid red line is not a good fit. I looked at a few sample data sets and saw issues with the default model scripts in these data sets:   2x3x4 factorial Bounce data Wine data Below is a plot of the 2x3x4 factorial Residual Normal Quantile Plot. I've been told that the slope of the solid red line is based on the RMSE of 2.02.     If I save the residuals to a new column and regenerate the Normal Quantile Plot from the Distribution plot, the line is based on the standard deviation of the Residual Y column of 1.03. It looks like a much more sensible fit from a model diagnostics perspective.   Is this something that can be updated in future versions of JMP? Note that when you use Fit Mixed, the results in the Residual Plots there match my desired result from manually saving the residuals to a new column. ... View more

What inspired this wish list request?  I wanted to compute the uncertainty of prediction fastly and easily for predictive model without using bagging. Indeed, bagging is quite slow to compute with the profiler.   What is the improvement you would like to see?    I would like to save the all the trees formula when I use the Bootstrap Forest Plateform. Or at least the standard deviation of the distribution.     Why is this idea important?    This is very important for me to be able to compute acquisition function when I do Surrogate Model Optimization (Bayesian Optimization). I tried to use bagging with the partition plateform, but the result is not satisfactory. The gaussien process plateform do not deal with categorical variable.     ... View more

What inspired this wish list request? I have been working my way through the excellent Visual Six Sigma: Making Data Analysis Lean (Wiley and SAS Business Series) (2016) book by Cox Gaudard and Stephens from SAS Institute.   I decided to test out the new Easy DOE platform on the example for reproducing the Anodize_CustomDesign_Results.jmp data.  (I had recently been able to reproduce the results with JMP step by step.)  This was quite easy and proved the power of the Easy DOE platform, both very visual and versatile with Guided Mode and Flexible Mode (it feels a bit like TurboTax modes).   Everything went well till the 6th of 7 steps in Easy DOE which is the Predict Step.  In this step, the profiler should show the grid for the effect of the 5 factors on the 4 outcome variables, plus the desirability row and column.    The 4 desirability row and 5 desirability column grid results are missing from the output even though the option is turned on in the red triangle.  When I tried to run the option of Maximize Desirability, this did indeed work well and gave the expected result.   But as I said previously the graphical output of the Desirability is missing from the grid.  (I am running the latest version of JMP 17.2.0)     What is the improvement you would like to see?  That not only can I maximize desirability, but also see the Desirability Functions as I already can outside of Easy DOE.   If you consider this suggestion makes the Guided Mode too busy visually, at least show the Desirability Functions in the grid in the (more advanced) Flexible Mode.     Why is this idea important? One of the most useful features of the Profiler is visualizing the Desirability Functions.  They permit visual sensitivity analysis, suggest trade-offs among (nearly) optimal solutions, etc. So I think that practitioners and students learning JMP can greatly benefit.     ... View more

What inspired this wish list request?  Trying to use Space Filling with a mixture that does not sum to 1.   What is the improvement you would like to see?  Add an option similar to that in Custom Design to change the mixture sum.   Why is this idea important?  There are workarounds, but they add a lot of unnecessary complexity.   ... View more

What inspired this wish list request? JMP is a great tool to help engineers and scientists use statistical methods with the best recommended options/choices. I have learned a lot with JMP about statistical methods and available method choices, and I'm very satisfied by the recommended options in some platforms (for example REML method for models involving random effects).  The "Augment design" platform is excellent. The different augmentation choices make the platform very powerful and convenient in a lot of use cases. However, I'm surprised to see that the option "Group new runs into separate block" is not checked by default, as this is a safe (and good) practice to check if there are any shift in the mean response between the first set of experiments and the next ones.    What is the improvement you would like to see?  I would like the option "Group new runs into separate block" checked by default, so that new users benefit from this safe practice when modeling the augmented DoE dataset. I wanted to change this in platforms preferences, but I wasn't able to find it ? I know this option makes the Space-Filling augmentation unavailable, but an information message just below the Space-Filling panel ("not available when using block") or below the "Group new runs..." option could help and inform the user why this option is greyed out.   Why is this idea important? As JMP promotes good and safe practices in statistics/modeling, I think it is important to recommend by default a safe and good practice in DoE augmentation. It can also help prevent any "bad surprises" when analyzing results for new DoE practicioners/beginners.     ... View more

  What inspired this wish list request? JMP does not seem to have a built-in support for zero-inflated models?    What is the improvement you would like to see? Possibility to fit zero-inflated model in JMP   Why is this idea important? It occurs quite often that the response is zero-inflated. Zero-inflated models are used when the response variable has a large number of zero values and a continuous, non-negative distribution for the non-zero values. Zero-inflated models combine two separate models: one for predicting the probability of a zero outcome, and another for predicting the non-zero values.     ... View more

With the increase in speed of deployment and usefulness of AI tools like ChatGPT could JMP use this as part of EasyDoE and other platforms to help users design an experiment as well as the analysis   Using a simple chat window linked to the AI it could ask you questions about the factors, constraints etc and this could then use JMP to build up the design of the experiment. Other companies are taking this approach to AI.   AI seems to be the future and integrating it into tools like JMP will be essential for the growth of data analytics in the (very near) future. Not implementing this soon could mean users look elsewhere for the simplicity of interactions with AI.     ... View more

What inspired this wish list request? Thanks for updating the interactive HTML output (File > Export >  Interactive HTML with data) in JMP for sharing results with colleagues! I use it many times and it really is a great feature! When I create a scatterplot matrix based on simulated data I like to filter my data. I can do this also within the HTML file output with the mouse by drawing a rectangle across the data points.     What is the improvement you would like to see? It would be much more intuitive to do this via the Local Data Filter. This feature is however not interactive in the HTML output. Could you fix that?     Why is this idea important?  Easier data & result sharing; onboarding new people to JMP       ... View more

What inspired this wish list request?  Model selection is essential for DoE Analysis. JMP provides this feature for platforms like Fit Stepwise or Generalized Regression, where only fixed effects are present in the model. However, by using Split Plot Designs or random block models I need to use either the Mixed Model Platform or the Generalized Mixed Model Platform. Both platforms does not allow automatic model selection steps like Backward Elimination, Forward Selection or Prune Forward Selection. Thus, I'm forced to perform these steps in a manually way, which are very tedious. Other software tools like Design Expert already allow automatic model selection for split plot designs!     What is the improvement you would like to see? Simply add all the model selection features from the generalized regression platform (see screenshot) to the Generalized Mixed Model Platform       Why is this idea important? At the moment I have to use Design Expert to perform a model selection on Split-Plot Designs, because it is too much work to do this manually in JMP. In other words, I cannot use JMP for Split-Plot Model Analysis respectively not even for random block models!     ... View more

I was walking an engineer through the Custom DOE platform. As part of our discussion, we decided to add a factor. The team wanted it to be the 2nd factor in the list of 5 factors, 4 of which were already carefully typed into the Custom DOE platform. We could not drag the new factor from the bottom of the list to the middle.    The engineer did not want to have to delete and reenter all of the factors. Given this, I did not suggest saving the factors table and reordering that.   We ended up creating the DOE table and moving the column in the table. But it was irritating. This seems like  simple thing to be able to do.   In Custom DOE and all of the other DOE platforms, I would like to be able to click and drag a factor (or response) up or down to another spot in the list of factors (or responses). This will save frustration, especially for those new to the DOE platforms.       ... View more

Hi!  I think it would be great to have the possibility to visualize a surface profiler plot within the Easy DoE platform. Since it is possible to design RSM, it would make sense to also be able to see these results in that specific profiler.  ... View more

What inspired this wish list request?  Process characterization reports often include prediction formulas and simulations.      What is the improvement you would like to see? Option to include prediction formulas in the easy DOE report export. Also would like to be able to export models/prediction and PredSE formulas to a jmp table from the easyDOE.   Why is this idea important? Because models made by an easyDOE user may need more exploration by advanced users. For example, comparing an easyDOE model to one made a different way, simulations, simple plots against data, etc. Typing prediction formulas with lots of factors is other non-trivial.      ... View more

What inspired this wish list request?      What is the improvement you would like to see? Add a quick blurb about the DOE method, JMP version, etc. to easy DOE reports     Why is this idea important?      ... View more

Hello,   I would like to request the following additions for the Color Maps for Correlations in the DOE platforms:   - Currently, the Special Purpose designs (e.g., Space-filling) do not have the option to generate a color map for correlations, unlike more traditional platforms such as Custom DOE. Can this be added? - When using the Compare Designs platforms, the color map block does not have a hot-key menu to change the color scheme from grayscale to blue-gray-red. Can this feature be added? I understand that there is currently a workaround available to customize the color scheme from the menu obtained when right-clicking on the map.   Thanks and regards Mehul Shroff   cc: @PatrickGuiliano ... View more