I recently updated my R version to the latest including all of the packages. After the update, the LOO function does not work anymore. I have saved a workspace with estimated models and previously I was able to estimate both LOO and WAIC for all of the models but now I get the error for one model if I try to run LOO on the fitted brms object. The error is the following: “Error: Can’t mix NA and not NA values in ‘r_eff’.”.

I fitted the model again, but the problem remains.

Please also provide the following information in addition to your question:

Hi! How can I provide a reproducible example? The non-working issue (for me) seems totally random as for some models it works well but for certain estimations it gives an error. WAIC I can estimate. The output for the same model:

waic(localrd_stud)

Computed from 4000 by 5044 log-likelihood matrix

Estimate SE

elpd_waic -33858.4 1852.1
p_waic 939.8 121.3
waic 67716.7 3704.1
Warning message:
234 (4.6%) p_waic estimates greater than 0.4. We recommend trying loo instead.

loo(localrd_stud)
Error: Can’t mix NA and not NA values in ‘r_eff’.

Probably I am doing something wrong but re-estimating did not solve the issue. In addition, with the older version, I was able to estimate the loo for all of the brmsfit objects.

I ran the models again. For smaller sub sample (n=594) both Loo and Waic statistics are calculated as they should. However for the second, bigger (n=6327), sample I can only compute WAIC, but not loo. The error remainds the same:

loo(localrd_stud)
Error: Can’t mix NA and not NA values in ‘r_eff’.
waic(localrd_stud)

Hi Paul, I am having the same issue when I try to call the loo function through brms on my glmms with 3864 observations. The waic function still works.

Thanks! Apparently I changed this in one place but not in another. It should now apply to all cases, but I didn’t check it with the code you provided. Would you mind testing it yourself with the latest github version of brms?

I am also getting this error, with the github version. My regression was fitted with model weights, any case that that has not been fixed? Let me know if you need the data and code. Thanks!