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JMP Wish List

We want to hear your ideas for improving JMP software.

  1. Search: Please search for an existing idea first before submitting a new idea.
  2. Submit: Post your new idea using the Suggest an Idea button. Please submit one actionable idea per post rather than a single post with multiple ideas.
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We consider several factors when looking for what ideas to add to JMP. This includes what will have the greatest benefit to our customers based on scope, needs and current resources. Product ideas help us decide what features to work on next. Additionally, we often look to ideas for inspiration on how to add value to developments already in our pipeline or enhancements to new or existing features.

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0 Kudos

Build in the option to see data in the profiler and to choose between displaying confidence intervals and prediction intervals.

What inspired this wish list request? Please describe the current issue that needs improvement or the problem to be solved that is not easy or possible right now, with an example use case. 

 

The idea was inspired by Figure 2.6 (seen below) from John K. Krushke's book Doing Bayesian Analysis, which displays a posterior predictive check.

mminor_3-1710267210439.png

 

What is the improvement you would like to see? Please describe the idea for improving JMP. Please include mock-ups, wireframes, screenshots, scripts, other documents or examples from other software that help describe the change you would like to see. 

 

I'd like to have the option to display data and the prediction intervals in Fit Model and Fit Y by X platforms to generate plots such as the example below. If these options were accessible from the red triangles that would be ideal.

mminor_1-1710264977725.png

 

Why is this idea important? Please describe the value to you and/or other users if the idea is implemented (for example, ease of use, must have,…).

 

The posterior predictive check allows one to see if the model mimics the data with reasonable accuracy. By overlaying data and prediction intervals on the profiler, we would be able to do a non-Bayesian version of the posterior predictive check. This would help us identify differences between the model and the data, including the error term of the model.

 

 

3 Comments
hogi
Level XI
mminor
Level I

Thanks for making me aware of the upcoming changes, it looks awesome!

mia_stephens
Staff
Status changed to: Delivered

Thank you for the request, and thanks @hogi for sharing the link. This new functionality is available in JMP 18, so marking this wish as Delivered.