Memory Leak?
Posted: 09 May 2025, 23:43
I have experienced some system problems estimating a hybrid choice mixed logit model. The code is long, so not including, and have not had the time to try and reproduce it with a code segment and simulated data.
I am running R through Rstudio on a Ubunto 22.04.5 LTS operating system, on a Dell Precision 3660 with an Intel i7-13700K processor (16 cores, 24 threads).
I have two versions of a model I am estimating. In one, I have a latent variable with a normal distribution, with nine indictors (7 point Likert, fit assuming normal) and 9 explanatory variables (dummy indicators). In the second, I add four random parameters.
I first ran the models with 100 draws. Worked. I increased the draws to 1000. Estimation stalled at the covariance matrix calculation (hours, no progress). I dropped it to 300, and it worked. I increased it to 500 and it again stalled. In this case, the stalling crashed Chrome and blanked the Rstudio window. In one attempted run, it locked up the entire machine. I am setting the number of cores to be `r trunc(0.8*availableCores()) '.
Not sure if this is an Apollo problem or an R problem.
John.
I am running R through Rstudio on a Ubunto 22.04.5 LTS operating system, on a Dell Precision 3660 with an Intel i7-13700K processor (16 cores, 24 threads).
I have two versions of a model I am estimating. In one, I have a latent variable with a normal distribution, with nine indictors (7 point Likert, fit assuming normal) and 9 explanatory variables (dummy indicators). In the second, I add four random parameters.
I first ran the models with 100 draws. Worked. I increased the draws to 1000. Estimation stalled at the covariance matrix calculation (hours, no progress). I dropped it to 300, and it worked. I increased it to 500 and it again stalled. In this case, the stalling crashed Chrome and blanked the Rstudio window. In one attempted run, it locked up the entire machine. I am setting the number of cores to be `r trunc(0.8*availableCores()) '.
Not sure if this is an Apollo problem or an R problem.
John.