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Hey,
since RM uses Java's Random generator there should not be any difference across machines if you set all random seeds to a fixed one. I think the only case where it might differ is 32bit vs 64bit, but this should nowadays only be a thing for edge devices.
Best,
Martin
Thx Martin. Have been observing differences between my laptop, the classroom podium machines (both 64-bit) and some student machines (varies) and have not been able to understand why. I wondered if the PRNG also uses some hardware characteristic like the motherboard serial numbers during seeding that could explain the observed differences (e.g, during sampling, data partitioning).
Hi Martin: I am pretty sure. We all (self and students) picked specific local seed values and some reported results different from the rest of the class. Last semester, I noticed differences between results on my home laptop and results on the podium machine with identical, to the best of my knowledge, process setups. I assumed that RMS was acting up on the podium (as sometimes Excel and Tableau also do) and college tech support opined that it perhaps was because I am not an administrator on the classroom podium machines. But I wondered why. This semester, I am polling students repeatedly to find out if anybody sees results different from the others when we use the Local PRNG. I will see if I can pinpoint the problem as occurring without plausible explanation (e.g., did the student do something different that caused this?) and report back to you. We just got started on RMS and I'll know more as the semester progresses and we get started on projects. Thanks much for the feedback -- I'll be sure to track this more carefully.
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Hey,
since RM uses Java's Random generator there should not be any difference across machines if you set all random seeds to a fixed one. I think the only case where it might differ is 32bit vs 64bit, but this should nowadays only be a thing for edge devices.
Best,
Martin