Hi everyone, I am wondering if anyone has any insight on my problem. The data for analysis designed the four-way dataset and they are unbalanced. Number of Observations Read: 12852 Number of Observations Used: 8404 Number of Observations Not Used: 4448 Class Levels treat 2 location 18 year 7 variety 51 I use PROC HPMIXED with assumed to unstructured UN variance-covariance matrix and the result was correct, but now I want to assumed different variance-covariance matrix, and try use PROC MIXED or PROC HPLMIXED with e.g. type=FA(1) it doesn’t working. PROC MIXED PROC HPMIXED PROC HPLMIXED UN ERROR: The SAS System stopped processing this step because of insufficient memory. OK ERROR: PROC HPLMIXED does not support this model in the current release. FA(1) ERROR: The SAS System stopped processing this step because of insufficient memory. - ERROR: PROC HPLMIXED does not support this model in the current release. I try different modification of model and dataset (smaller number of observations) but the program generate the ERRORS and NOTE e.g. ERROR: Optimization routine cannot improve the function value. ERROR: G matrix is not positive definite. HPLMIXED does not support this in the current release. ERROR: Newton-Raphson with Ridging optimization cannot be completed. ERROR: Model is too large to be fit by PROC HPMIXED in a reasonable amount of time on this system. NOTE: At least one element of the gradient is greater than 1e-3. The GCONV= option modifies the relative gradient convergence criterion and lowering its value might help to reduce the gradient. NOTE: The estimated G matrix is not positive definite. What can I do to use different variance-covariance matrix for this dataset? Example model: proc HPMIXED data =Y3.year7; class treat location year variety; model yield = treat /s; random location /s; random variety /s; random location /solution subject=variety type=un; random variety /solution subject=treat type=un; random location /solution subject=treat type=un; random variety*treat*location /solution; random year year*variety treat*year location*year treat*year*variety treat*location*year location*year*variety location*year*variety*treat; run; Thank you for any help.
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