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PurpleBat
Level I

best way to solve a complex time series analysis?

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 REPLIES 2
jthi
Super User

Re: best way to solve a complex time series analysis?

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 

-Jarmo
PurpleBat
Level I

Re: best way to solve a complex time series analysis?

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

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