The reason i use glmnet is that it makes the handling of 400,000 observations easier to handle in terms of memory,
I am looking on sparse matrices but i dont understand how to build interacting using sparse matrices On Tue, Oct 25, 2011 at 12:34 PM, Marc Schwartz <marc_schwa...@me.com> wrote: > > On Oct 25, 2011, at 11:16 AM, Ben Bolker wrote: > >> Bert Gunter <gunter.berton <at> gene.com> writes: >> >>> >>> If I understand you correctly, it sounds like you need to do some reading. >>> >>> ?lm and ?formula tell you how to specify linear models for glm or glmnet. >>> However, if you do not have sufficient statistical background, It probably >>> will be incomprehensible, in which case you should consult your local >>> statistician. >>> >>> For glmnet, go to the linked references given in the Help file.There is no >>> such thing as AIC for these models, as they are penalized fits (with users >>> choosing the penalization tradeoff). Again, consult your local statistician >> >> Let me second Bert's concern, but in the meantime, if what you >> want are *all two-way interactions among variables, you can follow >> this example: >> >>> d <- data.frame(y=runif(100),x1=runif(100),x2=runif(100),x3=runif(100)) >>> gg <- lm(y~(.)^2,data=d) >>> names(coef(gg)) >> [1] "(Intercept)" "x1" "x2" "x3" "x1:x2" >> [6] "x1:x3" "x2:x3" >> >> >> I have done the example with continuous variables and with lm() here, >> but it should generalize easily to (1) a mixture of categorical and >> continuous variables and (2) other R modeling functions > > > > There is a difference with glmnet however vis-à-vis its handling of factors. > There is a recent discussion here: > > https://stat.ethz.ch/pipermail/r-help/2011-August/285905.html > > which covers the topic. Be sure to read the replies, including Martin's. > > HTH, > > Marc Schwartz > > ______________________________________________ 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.
