[Rd] mean relative differences from all.equal() (PR#9276)

[Marc Schwartz]

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, bchristo at email.arizona.edu 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