topic Re: GENMOD "Error in computing deviance function" for dist = gam in Statistical Procedures

GENMOD "Error in computing deviance function" for dist = gam

topkatz — Tue, 20 Nov 2012 18:55:06 GMT

Hi!

I set up a standard gamma regression in PROC GENMOD as follows:

PROC GENMOD DATA = &inds. (where = (&dv. > 0));
MODEL &dv. = &ivlist. / dist = gam;
OUTPUT OUT = &outds. p = pred_&dv.;
RUN;

and got the following response:

WARNING: The specified model did not converge.
ERROR: Error in computing deviance function.
NOTE: The scale parameter was estimated by maximum likelihood.

I then attempted to perform a standard OLS on this data (I just changed
the dist= value from "gam" to "nor"), and that converged successfully.

I assumed from standard practice that a gamma regression was appropriate
for this data (it's a typical insurance loss model). I did not transform
the dependent variable (or the regressors) beforehand.

Any ideas / feedback are welcome.

Thanks!

-- TMK --

Re: GENMOD "Error in computing deviance function" for dist = gam

SteveDenham — Wed, 21 Nov 2012 13:48:13 GMT

I would seriously consider changing the link from the default inverse to the log. I know it is not the canonical link, but it does restrict the parameters to a "proper" space. That is why the default link for the gamma distribution in PROC GLIMMIX is the log link.

Also, it is likely that the convergence criteria need some fiddling--more iterations are the most likely solution.

Steve Denham

Re: GENMOD "Error in computing deviance function" for dist = gam

topkatz — Mon, 26 Nov 2012 06:38:10 GMT

Thank you for the response! That's an interesting observation about the link function, I wonder why GLIMMIX uses a different default for the gamma? But I may try the log when I get the chance (I'm going to try the ITPRINT option first to see if I can get any more diagnostic info).

Re: GENMOD "Error in computing deviance function" for dist = gam

SteveDenham — Mon, 26 Nov 2012 14:43:16 GMT

Not sure if I have this right, but I think the log link will result in a constant coefficient of variation across values, while the inverse may not. My friend Google seems to think that a gamma distribution with a log link is a lot more common for econometric data, so if that is what you are looking at, it may be helpfult to switch. I would also strongly recommend searching the listserv archives for SAS-L. See what you can find from Dale McLerran and David Cassell.

Steve Denham