I don't know lme models very well, but if you have standard errors for your
values, this shouldn't be too hard (as a last resort) using polygon()
x = 1:10
y = x^2
y.Err = 2*x
y.Up = y + y.Err; y.Dn =y-y.Err
# This graph is actually quite ugly so don't copy the formatting....
# Use the rev commands so the border moves logically around the shaded area
lines(x,y,type="b",lwd=3) # put the means back on top of the polygon
Still, this is a little brute force and I'd imagine that someone else will
shortly let you know how R can already do automatically.
On Mon, Aug 8, 2011 at 1:07 PM, bjmjarrett wrote:
I�m trying to plot confidence intervals for the fitted values I get with my
lme model in R.
Is there any way I can plot this in the form of a shaded band, like the
output of geom_smooth() in ggplot2 package. ggplot2 seems to use only lm,
glm, gam, loess and rlm as smoothing methods.
Any advice on the functions I should use to accomplish this will be very
Thank you very much.
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