This topic has come up a few times recently, so it must be 'in the wind'
these days. Depending on what approach you take and what area you are
coming
from, it goes under the names Orthogonal [Distance] Regression, Total
Least
Squares, Errors in Variables, Deming Regression. The middle two
encompass
much more in statistics terms (and I don't know what Deming did for
sure.)
If you have just two variables and you assume they are observed without
error, then the regression slope is just the ratio of the standard
deviations with the sign of the correlation coefficient, and the line
passes
through the means. There are assumptions about the errors that will
produce
the same result as a 'best linear fit,' but these assumptions about the
errors may not fit your situation. Do some reading in the TLS / EIV
arena to
see if you really want bald ODR.
HTH,
David L. Reiner
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-
> bounces at stat.math.ethz.ch] On Behalf Of Vito Ricci
> Sent: Friday, July 08, 2005 4:14 AM
> To: r-help at stat.math.ethz.ch
> Subject: [R] Orthogonal regression
>
> Dear R-Users,
>
> is there any statement to fit a orthogonal regression
> in R environment?
>
> Many thanks in advance.
>
> Best regards,
>
> Vito
>
>
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