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"?
Also, what do you know about "ODRpack"? It looks like that might
solve "the least (orthogonal) distance".
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
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