[R] Plotting a smooth curve from predict
Gavin Simpson
gavin.simpson at ucl.ac.uk
Tue Jul 31 13:21:36 CEST 2007
On Tue, 2007-07-31 at 11:21 +0100, Wilson, Andrew wrote:
> Probably a very simple query:
>
> When I try to plot a curve from a fitted polynomial, it comes out rather
> jagged, not smooth like fitted curves in other stats software. Is there
> a way of getting a smooth curve in R?
>
> What I'm doing at the moment (for the sake of example) is:
>
> > x <- c(1,2,3,4,5,6,7,8,9,10)
>
> > y <- c(10,9,8,7,6,6.5,7,8,9,10)
>
> > b <- data.frame(cbind(x,y))
>
> > w <- gls(y ~ I(x)+I(x^2),correlation=corARMA(p=1),method="ML",data=b)
>
> > plot(predict(w),type="l")
replace the line above with the following:
pred.dat <- data.frame(x = seq(min(x), max(x), length.out = 100))
plot(predict(w, pred.dat), type = "l")
The general idea is to produce predictions over the range of x, so we
produce a new data frame with component x, that contains 100 values from
min(x) to max(x). We then get predicted values for each of these new
values of the predictor in pred.dat, and plot them
Increase/decrease length.out to get something suitably smooth without
sending your computer into meltdown.
HTH
G
>
> Many thanks,
>
> Andrew Wilson
>
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