Performance of gaussian modelsHi,
I got a customer question about gaussian model's performance compared to Python. He says the data he is analyzing needs several seconds in Python but hours in JMP. Unfortunately I do not have many details about his data, it is about tens of thousand rows and may 20 columns. They wonder if in JMP Pro the performance would be different.
- As far I know JMP and JMP Pro are using the same algorithm and there is nothing different implemented which would have impact on the performance, correct?
- What could affect performance of the gaussian model algorithm in JMP that it seems to be that much slower than in Python? It does not seem to me that RAM and memory swapping might be the issue?
Thanks for some guidance,
Martin
PS: I will also ask the customer to work with Tech Support to see if there is some other reason.
@chris_gotwalt1
Re: Performance of gaussian modelsHi Martin,
There is definitely a difference between JMP and Pro. Pro has Fast GASP. I don't know if that will be as quick as Python but it should be an improvement version standard JMP.
Cheers,
Phil
Re: Performance of gaussian models@martindemel I think you should send this to Tech Support and let them investigate. It may be there is an issue that needs to be addressed.
Re: Performance of gaussian models@SamGardner Have done this as well 
Re: Performance of gaussian modelsHi @martindemel ,
as @Phil_Kay says, there is a different algorithm in Pro. I had a similar request from Syngenta this year, and the solution to increase speed in this case was as simple as to buy JMP Pro . Same machine, just JMP Pro.
Best
Florian
Re: Performance of gaussian modelsSo often the solution is buy JMP Pro. 
