Variational Inference output.csv from CmdStan

Interfaces CmdStan
1
  • Operating System: macOS Mojave 10.14.5
  • CmdStan Version: cmdstan-2.19.1.tar.gz
  • Compiler/Toolkit: g++ version 4.2.1

From the terminal, I ran:
> ./model variational data file=model.data.R
Output:

Begin eta adaptation.
Iteration:   1 / 250 [  0%]  (Adaptation)
Iteration:  50 / 250 [ 20%]  (Adaptation)
Iteration: 100 / 250 [ 40%]  (Adaptation)
Iteration: 150 / 250 [ 60%]  (Adaptation)
Iteration: 200 / 250 [ 80%]  (Adaptation)
Iteration: 250 / 250 [100%]  (Adaptation)
Success! Found best value [eta = 0.1].

Begin stochastic gradient ascent.
  iter             ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
   100     -3346380.401             1.000            1.000
   200      -834374.132             2.005            3.011
   300      -281093.666             1.993            1.968
   400      -127945.176             1.794            1.968
   500       -10989.192             3.564            1.968
   600        24816.866             3.210            1.968
   700        40843.712             2.808            1.443
   800        49501.247             2.479            1.443
   900        53522.280             2.212            1.197
  1000        56087.830             1.995            1.197
  1100        57740.509             1.898            1.197   MAY BE DIVERGING... INSPECT ELBO
  1200        58568.968             1.598            0.392   MAY BE DIVERGING... INSPECT ELBO
  1300        58767.108             1.402            0.175   MAY BE DIVERGING... INSPECT ELBO
  1400        59519.065             1.283            0.075   MAY BE DIVERGING... INSPECT ELBO
  1500        59821.387             0.219            0.046
  1600        59824.313             0.075            0.029
  1700        60547.624             0.037            0.014
  1800        60377.420             0.020            0.013
  1900        60825.661             0.013            0.012
  2000        60901.183             0.009            0.007   MEAN ELBO CONVERGED   MEDIAN ELBO CONVERGED

Drawing a sample of size 1000 from the approximate posterior... 
COMPLETED.

In RStudio, I ran:

> fit_VI <- read_stan_csv('output.csv')

Output:

Error in numeric(iter.count) : vector size cannot be NA

I cannot get Excel to open output.csv (size 9.22 GHB) either.