Hi David,
I don´t know if I got what you are looking for.
But see the code below.

x<-1:100
y<-x+(runif(100)*x)

plot(y~x)

mymod<-glm(y~x)

my.coefs<-coef(mymod)
my.coefs

curve(my.coefs[1]+my.coefs[2]*x, lwd=2, col="red", add=T)

Cheers,

mitinho astronauta
brazil
On Wed, Sep 10, 2008 at 6:06 PM, David Epstein
<David.Epstein@warwick.ac.uk>wrote:

>
> Suppose x and y are numeric vectors of the same length.
>
> plot(x,y) #scatterplot
> lmObj1 <- lm(y~x) # best fit line
> abline(lmObj1) # good
> lmObj2 <- lm(x~y) #get best fit but with axes interchanged
> abline(lmObj2) # not what I want. I want the correct line, drawn on the
> same
> graph, but with
>                    # response and predictor variables interchanged
>
> One way to proceed would be to extract the intercept and slope from lmObj2
> and then do the arithmetic to draw the correct line. I'm hoping for a more
> streamlined method. Is there one?
>
> Thanks
> David
> --
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