[R-sig-ME] How to use all the cores while running glmer on a piecewise exponential survival with

Adam Mills-Campisi @d@mmill@c@mpi@i @ending from gm@il@com
Thu Aug 23 21:30:55 CEST 2018

We originally tried to use stan to estimate the model, we were getting
performance issues. I assumed that the frequentist approaches would be

On Thu, Aug 23, 2018 at 12:28 PM Doran, Harold <HDoran using air.org> wrote:

> No. You can change to an improved BLAS or I have found the Microsoft R has
> some built in multithreading that is fast for matrix algebra and it passes
> that benefit to lmer. From some experience, you can improve computational
> time of an lmer model with Microsoft R
> -----Original Message-----
> From: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> On
> Behalf Of Adam Mills-Campisi
> Sent: Thursday, August 23, 2018 3:18 PM
> To: r-sig-mixed-models using r-project.org
> Subject: [R-sig-ME] How to use all the cores while running glmer on a
> piecewise exponential survival with
> I am estimating a piecewise exponential, mixed-effects, survival model
> with recurrent events. Each individual in the dataset gets an individual
> interpret (where using a PWP approach). Our full dataset has 10 million
> individuals, with 180 million events. I am not sure that there is any
> framework which can accommodate data at that size, so we are going to
> sample. Our final sample size largely depends on how quickly we can
> estimate the model, which brings me to my question: Is there a way to
> mutli-thread/core the model? I tried to find some kind of instruction on
> the web and the best lead I could find was a reference to this list serve.
> Any help would be greatly appreciated.
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