On 11-10-25 01:35 PM, julien giami wrote: > 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 >
If you're not familiar with glmnet but you are familiar with GLMs in general may I suggest bigglm() in the biglm package? > > > 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.
