> On Jun 17, 2017, at 12:01 PM, Jeff Newmiller <jdnew...@dcn.davis.ca.us> wrote: > > I have no direct experience with such horrific models, but your formula is a > mess and Google suggests the biglm package with ffdf. > > Specifically, you should convert your discrete variables to factors before > you build the model, particularly since you want to use predict after the > fact, for which you will need a new data set with the exact same levels in > the factors. > > Also, your use of I() is broken and redundant. I think formulas > > lny ~ id + year + x1 + I(x1^2) + x2 + I(x2^2) > > or > > lny ~ id + year + x1^2 + x2^2
This was offered as a formula to `felm` (but with no data example), a package with which I have no experience either, but if experience with `lm` and `glm` is any guide, an inferentially safer approach might be: lny ~ id + year + poly(x1,2) + poly(x2,2) -- David > > would obtain the intended prediction results. > > -- > Sent from my phone. Please excuse my brevity. > > On June 17, 2017 11:24:05 AM PDT, Miluji Sb <miluj...@gmail.com> wrote: >> Dear all, >> >> I am running a panel regression with time and location fixed effects: >> >> ### >> >> reg1 <- lm(lny ~ factor(id) + factor(year) + x1+ I(x1)^2 + x2+ I(x2)^2 >> , >> data=mydata, na.action="na.omit") >> ### >> >> My goal is to use the estimation for prediction. However, I have 8,500 >> IDs, >> which is resulting in very slow computation. Ideally, I would like to >> do >> the following: >> >> ### >> reg2 <- felm(lny ~ x1+ I(x1)^2 + x2+ I(x2)^2 | id + year , data=mydata, >> na.action="na.omit") >> ### >> >> However, predict does not work with felm. Is there a way to either make >> lm >> faster or use predict with felm? Is parallelizing an option? >> >> Any help will be appreciated. Thank you! >> >> Sincerely, >> >> Milu >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> 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 -- To UNSUBSCRIBE and more, see > 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. David Winsemius Alameda, CA, USA ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
