If you use loess instead of lowess, you can get standard errors and
hence approximate confidence bands by using predict.
Example:
plot(cars)
plx<-predict(loess(dist~speed, data=cars), se=T)
lines(cars$speed,plx$fit)
lines(cars$speed,plx$fit+2*plx$s, lty=2) #rough & ready CI
lines(cars$speed,plx$fit-2*plx$s, lty=2)
Mind you, there's absolutely no reason why adjacent values of y should
have anything to do with one another unless the x-axis is meaningful. I
assume your RI's were all collected in some meaningful equi-spaced
sequence or your x has both x- and y- components, 'cos there wouldn't be
much meaning to plot(lowess(RI)) otherwise.
Steve E
>>> "Gareth Campbell" <[EMAIL PROTECTED]> 05/08/2008 05:37 >>>
Hi there,
I'm plotting some glass RI values just by plotting
plot(x)
then I put on my lowess smoother
lines(lowess(x))
now I want to put on some 95% Confidence Interval bands of the lowess
smoother, but don't know how??
Thanks
--
Gareth Campbell
PhD Candidate
The University of Auckland
P +649 815 3670
M +6421 256 3511
E [EMAIL PROTECTED]
[EMAIL PROTECTED]
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