Fail to store residual for cross-classified model

Welcome to the forum for R2MLwiN users. Feel free to post your question about R2MLwiN here. The Centre for Multilevel Modelling take no responsibility for the accuracy of these posts, we are unable to monitor them closely. Do go ahead and post your question and thank you in advance if you find the time to post any answers!

Go to R2MLwiN: Running MLwiN from within R >> http://www.bris.ac.uk/cmm/software/r2mlwin/
Post Reply
vivian1234
Posts: 30
Joined: Tue Apr 12, 2016 10:54 am

Fail to store residual for cross-classified model

Post by vivian1234 »

Hi, I am running a cross-classified cumulative logit model for my ordinal outcome.
I used the following codes to store the residual:

Code: Select all

estoptions = list(resi.store = TRUE, resi.store.levs = c(2, 3, 4), xc = TRUE, EstM = 1
However, I have this error:
Error: memory exhausted (limit reached?)

In this case, how should I store the residual for residual diagnostic?

Thanks a lot.

Vivian
ChrisCharlton
Posts: 1351
Joined: Mon Oct 19, 2009 10:34 am

Re: Fail to store residual for cross-classified model

Post by ChrisCharlton »

To ensure the maximum amount of memory is available you could check that you are running a 64-bit version of R, as well as removing unneeded objects from memory (you can list the current objects with the ls() function).

If there still isn't space then you might want to consider whether you need the chains for all of the residuals. You could reduce the information stored by limiting the levels for which you store residual chains or by specifying a thinning value.
vivian1234
Posts: 30
Joined: Tue Apr 12, 2016 10:54 am

Re: Fail to store residual for cross-classified model

Post by vivian1234 »

Thanks a lot.
Post Reply