From: Ole Edsberg <edsberg_at_stud.ntnu.no>

Date: Mon 30 Jan 2006 - 19:39:15 EST

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 Received on Mon Jan 30 19:48:25 2006

Date: Mon 30 Jan 2006 - 19:39:15 EST

Hello,

I have a data set on which I run the sammon algorithm as follows:

library(MASS)

data = read.table('problemforr.dat')

y = cmdscale(data, add=TRUE)

s = sammon(data, y$points)

(In case it should be relevant, I make the data available at

http://idi.ntnu.no/~edsberg/problemforr.dat)

With R 2.2.1 on Debian Sid I always get one of two solutions (stress
1.74288 after 10 iterations or stress 1.33629 afer 9 iterations). I
always get the same result within the same R session, even if I read
the data again. With R 2.2.0 on SunOS 5.9 I always get the same result

(stress 0.13186 after 74 iterations).

I read in the documentation

(http://stat.ethz.ch/R-manual/R-patched/library/MASS/html/sammon.html)

that "Further, since the configuration is only determined up to
rotations and reflections (by convention the centroid is at the
origin), the result can vary considerably from machine to machine."
This doesn't make sense to me. If the data and the algorithm is the
same, the result should be the same. What differences between machines
do they refer to here? Floating point issues?

I must admit that I am a beginner, both in R and in statistics. I'm very curious about the cause of this strangeness. Does anybody have an explanation?

Best Regards,

Ole Edsberg

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 Received on Mon Jan 30 19:48:25 2006

*
This archive was generated by hypermail 2.1.8
: Fri 03 Mar 2006 - 03:42:14 EST
*