Dear Spencer, > -----Original Message----- > From: Spencer Graves [mailto:[EMAIL PROTECTED] > Sent: Sunday, May 29, 2005 4:13 PM > To: John Fox > Cc: r-help@stat.math.ethz.ch; 'Jacob van Wyk'; 'Eric-Olivier Le Bigot' > Subject: Re: [R] Errors in Variables > > Hi, John: > > Thanks for the clarification. I know that the > "errors in X problem" > requires additional information, most commonly one of the > variances or the correlation. The question I saw (below) > indicated he had tried "model of the form y ~ x (with a given > covariance matrix ...)", which made me think of "sem". > > If he wants "the least (orthogonal) distance", could > he could get it indirectly from "sem" by calling "sem" > repeatedly giving, say, a variance for "x", then averaging > the variances of "x" and "y" and trying that in "sem"? >
I'm not sure how that would work, but seems similar to averaging the regressions of y on x and x on y. > Also, what do you know about "ODRpack"? It looks > like that might solve "the least (orthogonal) distance". > I'm not familiar with ODRpack, but it seems to me that one could fairly simply minimize the sum of squared least distances using, e.g., optim. Regards, John > Thanks again for your note, John. > Best Wishes, > Spencer Graves > > John Fox wrote: > > > Dear Spencer, > > > > The reason that I didn't respond to the original posting (I'm the > > author of the sem package), that that without additional > information > > (such as the error variance of x), a model with error in > both x and y > > will be underidentified (unless there are multiple indicators of x, > > which didn't seem to be the case here). I figured that what > Jacob had > > in mind was something like minimizing the least > (orthogonal) distance > > of the points to the regression line (implying by the way > that x and y > > are on the same scale or somehow standardized), which isn't > doable with sem as far as I'm aware. > > > > Regards, > > John > > > > -------------------------------- > > John Fox > > Department of Sociology > > McMaster University > > Hamilton, Ontario > > Canada L8S 4M4 > > 905-525-9140x23604 > > http://socserv.mcmaster.ca/jfox > > -------------------------------- > > > > > >>-----Original Message----- > >>From: [EMAIL PROTECTED] > >>[mailto:[EMAIL PROTECTED] On Behalf Of > Spencer Graves > >>Sent: Saturday, May 28, 2005 4:47 PM > >>To: Eric-Olivier Le Bigot > >>Cc: r-help@stat.math.ethz.ch; Jacob van Wyk > >>Subject: Re: [R] Errors in Variables > >> > >> I'm sorry, I have not followed this thread, but I > wonder if you > >>have considered library(sem), "structural equations modeling"? > >>"Errors in variables" problems are the canonical special case. > >> > >> Also, have you done a search of "www.r-project.org" > >>-> search -> "R site search" for terms like "errors in > >>variables regression"? This just led me to "ODRpack", > which is NOT a > >>CRAN package but is apparently available after a Google > search. If it > >>were my problem, I'd first try to figure out "sem"; if that seemed > >>too difficult, I might then look at "ODRpack". > >> > >> Also, have you read the posting guide! > >>http://www.R-project.org/posting-guide.html? This suggests, among > >>other things, that you provide a toy example that a potential > >>respondant could easily copy from your email, test a few > >>modifications, and prase a reply in a minute or so. > >>This also helps clarify your question so any respondants are more > >>likely to suggest something that is actually useful to you. > Moreover, > >>many people have reported that they were able to answer their own > >>question in the course of preparing a question for this > list using the > >>posting guide. > >> > >> hope this helps. spencer graves > >> > >>Eric-Olivier Le Bigot wrote: > >> > >> > >>>I'm interested in this "2D line fitting" too! I've been looking, > >>>without success, in the list of R packages. > >>> > >>>It might be possible to implement quite easily some of the > >> > >>formalism > >> > >>>that you can find in Numerical Recipes (Fortran 77, 2nd ed.), > >>>paragraph 15.3. As a matter of fact, I did this in R but > >> > >>only for a > >> > >>>model of the form y ~ x (with a given covariance matrix > >> > >>between x and > >> > >>>y). I can send you the R code (preliminary version: I > >> > >>wrote it yesterday), if you want. > >> > >>>Another interesting reference might be Am. J. Phys. 60, p. > >> > >>66 (1992). > >> > >>>But, again, you would have to implement things by yourself. > >>> > >>>All the best, > >>> > >>>EOL > >>> > >>>-- > >>>Dr. Eric-Olivier LE BIGOT (EOL) CNRS > >> > >>Associate Researcher > >> > >>~~~o~o~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > >>~~~~o~o~~~ > >> > >>>Kastler Brossel Laboratory (LKB) > >> > >>http://www.lkb.ens.fr > >> > >>>Université P. & M. Curie and Ecole Normale Supérieure, Case 74 > >>>4 place Jussieu 75252 Paris CEDEX 05 > >> > >> France > >> > >>~~~o~o~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > >>~~~~o~o~~~ > >> > >>>office : 01 44 27 73 67 fax: > >> > >>01 44 27 38 45 > >> > >>>ECR room: 01 44 27 47 12 x-ray room: > >> > >>01 44 27 63 00 > >> > >>>home: 01 73 74 61 87 For int'l calls: 33 + number > >> > >>without leading 0 > >> > >>> > >>>On Wed, 25 May 2005, Jacob van Wyk wrote: > >>> > >>> > >>>>I hope somebody can help. > >>>>A student of mine is doing a study on Measurement Error models > >>>>(errors-in-variables, total least squares, etc.). I have an old > >>>>reference to a "multi archive" that contains > >>>>leiv3: Programs for best line fitting with errors in both > >> > >>coordinates. > >> > >>>>(The date is October 1989, by B.D. Ripley et al.) I have done a > >>>>search for something similar in R withour success. Has this been > >>>>implemented in a R-package, possibly under some sort of > >> > >>assumptions > >> > >>>>about variances. I would lke my student to apply some regression > >>>>techniques to data that fit this profile. > >>>>Any help is much appreciated. > >>>>(If I have not done my search more carefully - my > >> > >>apologies.) Thanks > >> > >>>>Jacob > >>>> > >>>> > >>>>Jacob L van Wyk > >>>>Department of Mathematics and Statistics University of > >> > >>Johannesburg > >> > >>>>APK P O Box 524 Auckland Park 2006 South Africa > >>>>Tel: +27-11-489-3080 > >>>>Fax: +27-11-489-2832 > >>>> > >>>>______________________________________________ > >>>>R-help@stat.math.ethz.ch mailing list > >>>>https://stat.ethz.ch/mailman/listinfo/r-help > >>>>PLEASE do read the posting guide! > >>>>http://www.R-project.org/posting-guide.html > >>>> > >>> > >>> > >>------------------------------------------------------------ > ---------- > >> > >>>-- > >>> > >>>______________________________________________ > >>>R-help@stat.math.ethz.ch mailing list > >>>https://stat.ethz.ch/mailman/listinfo/r-help > >>>PLEASE do read the posting guide! > >>>http://www.R-project.org/posting-guide.html > >> > >>______________________________________________ > >>R-help@stat.math.ethz.ch mailing list > >>https://stat.ethz.ch/mailman/listinfo/r-help > >>PLEASE do read the posting guide! > >>http://www.R-project.org/posting-guide.html > > > > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html