best way to solve a complex time series analysis?

[#1]

Hi there,

here is what I want to do (my JMP version is 19.0.3):

• I have a data set with >10 million rows, time series data
• I need to carry out a segmented fit for >1000 segments
• I know that I can do this in R, but not how to do this in JMP
• my aim is now:
  • have the data in JMP
  • carry out the segemented fitting in R
  • summarise the data into a new table
  • transfer the data back to JMP

The alternative is to work fully outside of JMP for the summary tables - but if this is possible I would like to try this within JMP and its R integration.

What would help me are: training resources / reading materials for R in JMP, and hints if you have done something like this already.

Thank you!

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[#2]

If I remember correctly, in JMP19, R integration is currently done via Python Integration. Here is one presentation of thatScripters Club Recording: R is Back Again in JMP 19 - Exploring R and Python Integration 

[#3]

Thank you @jthi, that's a good starting point!

[#4]

Hi @PurpleBat ,

To understand a bit more about what you're trying to achieve, what is the segmentation doing/what is the end goal? I segment the zones where there is activity (ie increasing Phil T1 Ave)?

If you can comment on the process in R or the package, it may be possible just to use JMP or even JSL to achieve the same thing.

Thanks,

Ben