Hi Kevin,
Intuitively, the first step would be to ensure that all versions of R,
and all the R packages, are the same.
However, you mention HPC.
And the glmnet package imports the foreach package, which appears
(after a quick glance) to support multi-core and parallel computing.
If your code uses parallel computing (?), you may need to look at how
random numbers, and related results, are handled...
On Sun, Aug 9, 2020 at 1:14 AM Kevin Egan <kevinega...@gmail.com> wrote:
I posted this question:
I am currently using R , RStudio , and a remote computer (using an R
script) to run the same code. I start by using set.seed(123) in all three
versions of the code, then using glmnet to assess a matrix. Ultimately, I
am having trouble reproducing the results between my local and the remote
computer's results. I am using R version 4.0.2 locally, and R version 3.6.0
remote.
After running several tests, I'm wondering if there is a difference
between the two versions in R which may lead to slightly different
coefficients. If anyone has any insight I would appreciate it.
Thanks.
and found that there were slight differences between using rnorm with
R-4.0.2 and R-3.6.0 but did not find any differences for runif between both
systems. In my original code, I am using rnorm and was wondering if this
may be the reason I am finding slight differences in coefficients for
glmnet and lars testing between using my local computer (R-4.0.2) and my
remote computer (R-3.6.0). I am running my code locally on a MacOSX and
remote on what I believe is an HPC.
Thanks.
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
