On 09/09/2013 08:48, Clara wrote:
Hi all,
I have an older, probably about 2 years old glm object, I am not sure
with which version of glm it was produced. I have tried to
Before R 3.0.0, which was a change in major version number.
summary(my.model) but I get an error.
> summary(my.model)
Error in .Call("binomial_dev_resids", y, mu, wt, PACKAGE = "stats") :
"binomial_dev_resids" not available for .Call() for package "stats"
Some info about the model:
Call: glm(formula = my.formula, family = binomial, data = my.data,
weights = my.weights,
x = T, y = T)
My current r version and platform:
R version 3.0.1 (2013-05-16) -- "Good Sport"
Platform: x86_64-pc-linux-gnu (64-bit)
I have used my.model before, about a year ago, without any problems. So
my questions are,
(1) Is there a way to "update" the model so it works with the new
version of summary.glm? or is there a way to make the new summary.glm
function agreeable to my.model?
It is not to do with summary.glm: it is AFAIK due to what is stored in
'my.model'. You should re-fit my.model.
In this particular case (which is not reproducible to us) it is possible
that
my.model$family <- binomial()
would work.
(2) Should I expect this behavior with other older models? I mean, If I
create a model today should I expect to have problems when I try to do
simple stuff with it, like "summary", in a couple of years?
Yes.
(3) Is there a way to prevent this? What would be the best way to make
sure, as much as possible, that the models I produce today will be
usable in the future by me and others?
Not save .RData files and expect them to work with an R with an
increased major version number.
You should regard .RData files as a permanent form of storage only for
data (things like data frames).
Any help is greatly appreciated. I will run into this problem again, so
I would very much appreciate any help on how to handle this.
Use the version of R you used to create the object my.model to explore it.
And BTW R 3.0.x has been out for several months and I have not seen
anyone one else reporting such a problem so I think it is much rarer
than you believe.
Clara
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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