On 07/09/2010 4:18 PM, Johann Hibschman wrote:
David Winsemius<dwinsem...@comcast.net> writes:> Just tested my theory and it seems to be holding up. Took the example > on the predict help page, set three of the variable length components > not needed in the predict operations to NULL and the code still runs > fine. It does not appear that either predict.glm or predict.lm check > to see if there are any missing components: Going through that code, I settled on the following function to remove all but the most needed components: ## Strip down a glm object, until it can only be used for prediction, ## but is nice and small. strip.glm<- function (f) { f.str<- list(coefficients=f$coefficients, family=f$family, terms=f$terms, qr=list(pivot=f$qr$pivot), rank=f$rank, na.action=f$na.action) attr(f.str$terms, ".Environment")<- globalenv() class(f.str)<- class(f) f.str }
I think a safer modification would be to set the environment to emptyenv(). That won't take any space, but it means if you miscalculated and some variables in that environment really were being used, you'll get an error instead of a wrong answer.
Duncan Murdoch
The truly enormous volume of data was coming in along with the environment in terms; setting that to the global environment shrunk the saved file down from 490 MB to 32 MB, which is about the size of the data matrix. Then stripping down the qr to just the pivot vector reduces the size to 2.8 KB. (Other components of the glm object were also bringing the environment along with them; I've not experimented to see which were the other offenders. terms was the only one that I needed.) Thanks for your help, Johann ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
