minimal attributes to get se.fit

Does anybody know what are the attributes of a glm fit object that will allow
the "predict call" to produce an se.fit?

....

I believe the covariance matrix of the coefficients is all that should be needed
and that is quite small. However, the covariance matrix is not an attribute of
the model object.

Try saving the summary object? That includes the covariances (scaled and unscaled). See ?summary.glm. It might also leave you with a smaller object, though I'm not sure about that.

Also note that on this list, when prediction from glm comes up, there's a strong likelihood that someone will point out that the covariances are not necessarily sufficient for reliable confidence intervals on prediction (and look! that just happened). You might want to hunt around for more authoritative comment on that if the intervals/standard errors  are critical for something .


S Ellison





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