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 mminor_3-1710267210439.png](https://community.jmp.com/t5/image/serverpage/image-id/62141i7912A13F81DD6FC5/image-size/medium?v=v2&px=400)
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 mminor_1-1710264977725.png](https://community.jmp.com/t5/image/serverpage/image-id/62135i65D2D28317C4B330/image-size/medium?v=v2&px=400)
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.