On Wed, 2006-10-04 at 21:57 -0500, Marc Schwartz wrote: > On Wed, 2006-10-04 at 20:22 -0500, Marc Schwartz wrote: > > On Thu, 2006-10-05 at 03:10 +0200, [EMAIL PROTECTED] wrote: > > > Full_Name: Brad Christoffersen > > > Version: 2.3.1 > > > OS: Windows XP > > > Submission from: (NULL) (128.196.193.132) > > > > > > > > > Why is the difference between two numbers so different from the "mean > > > relative > > > difference" output from the all.equal() function? Is this an artifact of > > > the > > > way R stores numerics? I could not find this problem as I searched > > > through the > > > submitted bugs. But I am brand new to R so I apologize if there is > > > something > > > obvious I'm missing here. > > > > > > rm(list=ls(all=TRUE)) ## Remove all objects that could hinder w/ > > > consistent > > > output > > > a <- 204 > > > b <- 203.9792 > > > all.equal(a,b) > > > [1] "Mean relative difference: 0.0001019608" > > > a - b > > > [1] 0.0208 > > > > Read the Details section of ?all.equal, which states: > > > > Numerical comparisons for scale = NULL (the default) are done by first > > computing the mean absolute difference of the two numerical vectors. If > > this is smaller than tolerance or not finite, absolute differences are > > used, otherwise relative differences scaled by the mean absolute > > difference. > > > > If scale is positive, absolute comparisons are made after scaling > > (dividing) by scale > > > > > > Thus on R version 2.4.0 (2006-10-03): > > > > > all.equal(a, b, scale = 1) > > [1] "Mean scaled difference: 0.0208" > > > > > > Please do not report doubts about behavior as bugs. Simply post a query > > on r-help first. If it is a bug, somebody will confirm it and you can > > then report it as such. > > > > BTW, time to upgrade...Go Wildcats! > > > > HTH, > > > > Marc Schwartz > > [OFFLIST and PRIVATE] > > Brad, > > A couple of comments. > > First, welcome to R. I hope that you enjoy it and find it of value. > > If you are not used to open source software and communities (ie. Linux, > etc.), you will find that this community, unlike commercial paid support > forums, tends to be direct with respect to comments. Don't take it > personally. > > Be aware that nobody is getting paid to support R. It is developed and > supported on a voluntary basis by a large body of folks, mainly those > known as "R Core". Some of them have quite literally risked their > academic careers and livelihood to facilitate R's existence. > > You will, over time, get a flavor for the nature of the community and > the interchange that takes place. As a result of the voluntary nature of > the community, there is an a priori expectation that you will have put > forth reasonable efforts to avail yourself of the various support > resources before posting. Especially in the case of a bug report, as a > member of R Core has to manually manage the handling and resolution of > bug reports. > > A good place to start is to review the R Posting Guide: > > http://www.r-project.org/posting-guide.html > > which covers many of these issues and how to go about getting support > via the various sources provided. > > That all being said, you will find that R's support mechanisms and > resources are second to none and I would challenge any commercial > software vendor to provide a comparable level of support and expertise. > > With respect to your specific question above and how the result is > obtained: > > > (a - b) / a > [1] 0.0001019608 > > Here, 'a' is used as the scaling factor, since you only passed single > values. If these were 'vectors' of values, the scaling factor would be > impacted accordingly. > > As a result of R's open source nature, you have access to all of the > source code that is R. You can download the source tarball (archive) > from one of the CRAN mirrors, if you so desire. > > In this case, the actual function that is used is called > all.equal.numeric(). This is a consequence of how R uses 'dispatch > methods' after a call to a 'generic' function, such as all.equal(). If > you are not familiar with these terms, the available R documentation is > a good place to start, if you should decide to pursue moving into that > level of detail. If you have experience in other programming languages, > this may be second nature already. > > In many cases, R's functions are written in R itself. Others are written > in FORTRAN and/or C that is compiled and linked to R via various calling > mechanisms. Since R is an interpreted language, you can have easy access > to many of the functions within the R console. > > Thus, at the R command prompt, you can type: > > > all.equal.numeric > > [Note without the parens] > > which will then display a representation of the function's source code, > enabling you to review how the function works. If you desire to become a > better R user/programmer, this approach provides a reasonable way to see > how functions are coded and to investigate algorithms and techniques. > > I hope that the above is helpful. > > Best regards, > > Marc
My most sincere and public apologies to Brad. The reply message above was mistakenly copied to the list. Brad I am sorry. Marc Schwartz ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
