[S] regression with uncertainty in both variables

[I don't think blanketing both S and R help on this is a good idea.]

I'm trying to use some linear regression models in which both the
dependent and independent variables are measured with some error.  To

Notation: that is not a `regression' model.

make things worse, while the errors in the dependent variable are uniform,
the errors in the independent (or explanatory, or "x") variables can be
heteroskedastic.  I've been looking at the book _Measurement Error Models_
by Fuller (1987).  I'm wondering whether anybody knows any other
references on the subject, and whether anyone has written S or R code that
handles these kinds of problems.  (As far as I can tell, the usual lm and
glm functions don't; if I'm wrong, that's great.)

Well, there are of lots of other references, even one by me, but that is
the main book. If lm and glm did this they would be wrong: it is a
different statistical model. There are several Fortran solutions on statlib
in multi/leiv?

1.      Programs for best line fitting with errors in both coordinates.

2.      D. York, "Least squares fitting of a straight line", Canadian 
                 Journal of Physics, 44, 1079-1086, 1986.
        G. Fasano and R. Vio, "Fitting straight lines with errors on both
                 coordinates", Newsletter of Working Group for Modern 
                 Astronomical Methodology, No. 7, 2-7, Sept. 1988.
        B.D. Ripley and M. Thompson, "Regression techniques for the 
                 detection of analytical bias", Analyst, 112, 377-383,
                 1987.

and I have seen an S interface somewhere (multiv?). Today, I would take the
algorithm in the last of those papers and re-write it in S in a few
minutes. A project that has, several times, nearly made the MASS library
and one I set as a exercise in my linear models course.

Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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