I think we can blame Tim Hesterberg for the confusion: He writes
" I'll add: * inverse-variance weights, where var(y for observation) = 1/weight (as opposed to just being inversely proportional to the weight) * " And, although I'm not a native English speaker, I think there's a spurious comma in there. The intention was clearly to have this as a 4th type of weight which is a special case of inverse-variance weights, not as an elaboration on the definition of inv.var. weights. I.e., it is the difference between Motorists who are reckless drivers... and Motorists, who are reckless drivers... -pd On 06 Feb 2014, at 16:04 , John Fox <j...@mcmaster.ca> wrote: > Dear Marco, > > What I said in the 2007 r-help posting to which you refer is, "The weights > used by lm() are (inverse-)'variance weights,' reflecting the variances of > the errors, with observations that have low-variance errors therefore being > accorded greater weight in the resulting WLS regression." ?lm says, > "Non-NULL weights can be used to indicate that different observations have > different variances (with the values in weights being inversely proportional > to the variances)." > > If I understand your situation correctly, you know the error variances up to > a constant of proportionality, in which case you can set the weights > argument to lm() to the inverses of these values. As I showed you in the > example I just posted, weight and 2*weight *do* produce the same coefficient > estimates and standard errors, with the difference between the two absorbed > by the residual standard error, which is the square-root of the estimated > constant of proportionality. > > If this is insufficiently clear, I'm afraid that I'll have to defer to > someone with greater powers of explanation. > > Best, > John > >> -----Original Message----- >> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- >> project.org] On Behalf Of Marco Inacio >> Sent: Thursday, February 06, 2014 9:06 AM >> To: r-help@r-project.org >> Subject: Re: [R] proportional weights >> >> Thanks for the answers. >> >>> Dear Marco and Goran, >>> >>> Perhaps the documentation could be clearer, but it is after all a >> brief help page. Using weights of 2 to lm() is *not* equivalent to >> entering the observation twice. The weights are variance weights, not >> case weights. >>> >> According to your post here: >> http://tolstoy.newcastle.edu.au/R/e2/help/07/05/16311.html >> there are 3 possible kinds of weights. >> >> The person in this one: >> http://tolstoy.newcastle.edu.au/R/e2/help/07/06/18743.html >> includes 2 others making a distinction between weights inverse >> proportional to variance and weight equal to inverse variance. >> >> (looking at other posts in the thread shows that other people also make >> confusions on this matter) >> >> So R's lm(), glm(), etc weights **are** the inverse of the variance of >> the observations, right? >> They'are not **proportional** to the inverse of variance because if >> this >> were true, then weight and 2*weight would archive the same results, >> right? >> >> >> I needed a method to use proportional weights on observations as I know >> their proportion of variance among each other. >> And it doesn't need to be a R function, just an explanation on how >> construct the likehood would be fine. If anybody know an article on the >> subject, would be of great help to. >> >> ______________________________________________ >> 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. -- Peter Dalgaard, Professor Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ 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.