On May 22, 2012, at 9:10 AM, Canto Casasola, Vicente David
wrote:>
> I'm pretty sure I'm missing something about this.
>
> Is there a smart way of typping hat(R)^2 and it's value from a linear
> regression?
>
> I've just found this tricky one:
>
> # Sample data
> x <- sample(1:100,10)
> y <- 2+3*x+rnorm(10)
>
> # Run the regression
> lm1 <- lm(y~x)
> # Plotting
> plot(x,y, main="Linear Regression", col="red")
> abline(lm1, col="blue")
> placex <-
par("usr")[1]+.1*(par("usr")[2]-par("usr")[1])
> placey1 <-
par("usr")[3]+.9*(par("usr")[4]-par("usr")[3])
> placey2 <-
par("usr")[3]+.8*(par("usr")[4]-par("usr")[3])
>
> # HERE: Is this the right way?
# To do .... what? I see that you over-plotted the R, presumably
because you did not like the way that:
bquote(hat(R)^2 == .(summary(lm1)$adj.r.squared))
... ended up looking (with the exponent higher than in the non-hatted
version.)
>
> text(x=placex, y=placey1,
> bquote(R^2 == .(summary(lm1)$r.squared)), adj=c(0,0))
> text(x=placex, y=placey2,
> bquote(R^2 == .(summary(lm1)$adj.r.squared)), adj=c(0,0))
> text(x=placex,y=placey2,
> expression(hat(R)), adj=c(0,0))
>
> In addition, when I save the plot as PDF, the expression hat(R)
> seems to be
> somewhat displaced.
>
> Any advice?
>
Are you sure? It "looks" to me that the lower "R" is
slightly shifted
to the left, but when I actually measure it, there does not appear to
be a shift. If it is real and not just an optical illusion, this may
have something to do with your unstated version of R or your also
unstated OS.
--
David Winsemius, MD
West Hartford, CT