So I did in fact go with Pluto.jl and was able to convert my Jupyter notebook by copying and pasting most of the code. The UI was the part that required adjustment, but it was relatively easy after reading some examples. It helped that I tried out Pluto back in 2020 when it first came out and had seen some JuliaCon videos at some point.
Here’s a screenshot using simulated data, the game is “adjust the sliders until the points are a cloud around y=0 for all x and all colors (age groups)”
From this starting point then, we can start optimization and expect it to come to a reasonable and meaningful optimum without being stuck in some strange corner of parameter space (where for example the point cloud looks like a V around 0 instead of a flat blob but any adjustment to any parameter makes the fit worse so the optimizer is stuck).
Thanks again ! and thanks to @fonsp and friends for all the great work on Pluto.