Thank you Bert, I wasn’t aware of ?str. The only mention of fitted-values is:
$ maximum : atomic [1:1] -9824 ..- attr(*, "fitted.values")= num [1:3460] 1.39 1.3 1.3 1.32 1.27 ... When I try attr(mymodel$maximum, ”fitted.values”), I get the same results as attr(AIC(mymodel), ”fitted.values”), which is a list of number starting with (1.39 1.3 1.3 1.32 1.27 …). I don’t see how these can be fitted values for the response variable, patents, which are larger numbers (30, 3, 48, 1, 2, 32, …). Is this output not supped to represent the fitted values for patents? Another way to obtain fitted values would be using residuals.?pglm also includes residuals in its list of elements. However, str(mymodel) does not mention residuals. Does that mean it’s just not there? - Simon > On Apr 12, 2019, at 10:44 AM, Bert Gunter <bgunter.4...@gmail.com> wrote: > > ?fitted > ?predict > ## This is what one usually does, but I have not checked pglm. > > You also need to get friendly with ?str > > ... and probably also spend time with an R tutorial or two to become familiar > with R modeling conventions. > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > On Fri, Apr 12, 2019 at 7:35 AM Simon Berrebi <si...@berrebi.net > <mailto:si...@berrebi.net>> wrote: > Hello everyone, > > I am using the pglm function in R to fit a Poisson fixed-effects model. > According to the documentation > <https://cran.r-project.org/web/packages/pglm/pglm.pdf > <https://cran.r-project.org/web/packages/pglm/pglm.pdf>>, the pglm object > should have fitted.values. However, fitted.values(mymodel) returns "NULL". > > When I run AIC(mymodel) the AIC is followed by "attr(,"fitted.values")" and a > long list of number. I have included an example below and attached a text > file with the output. > > Are these fitted values? If so, is there a way to obtain them directly? Can I > also get fitted-values based on a synthetic dataset (i.e. predict())? > > install.packages("pglm") > library(pglm) > > data("PatentsRDUS", package="pglm") > > > mymodel <- pglm(patents ~ log(rd) + as.numeric(year)+ > I(log(capital72)*as.numeric(year)) , PatentsRDUS, > family = poisson(link=log), model = "within", index = c("cusip", "year")) > > fitted.values(mymodel) > AIC(mymodel) > > Cordially, > — > Dr. Simon J Berrebi > Postdoctoral Fellow > Civil and Environmental Engineering > Georgia Institute of Technology > > > > > > > > > ______________________________________________ > R-help@r-project.org <mailto:R-help@r-project.org> mailing list -- To > UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > <https://stat.ethz.ch/mailman/listinfo/r-help> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > <http://www.r-project.org/posting-guide.html> > and provide commented, minimal, self-contained, reproducible code. [[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.
