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AndreaB_
Calcite | Level 5

Hi,

 

I want to use PROC MCMC to run a random-effects linear negative binomial (NB1) model and estimate ~200,000 random intercepts (as an alternative to NLMIXED).  Since the OUTPOST= dataset can only save up to 32,767 variables, what approaches can I take to be able to output the posterior samples for all of the ~200K random-effects parameters?

 

 

Thanks,

Andrea

 

P.S. I have SAS v9.4 (TS1M4) and SAS/STAT 14.2.

1 REPLY 1
Garnett
Obsidian | Level 7

Hi,

An easy way is to assume the posterior on each effect is Gaussian:

 

1) Monitor the posterior distributions of the random effects.

2) Write ODS output postsumint=Px;

3) In a subsequent datastep, sample from the mean and Standard deviation given in Px (or just use the posterior info in Px.)

 

Let me know if this isn't what you are thinking...

G

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