How can I use spline() with ggplot?

I would like to fit my data using spline(y~x) but all开发者_开发百科 of the examples that I can find use a spline with smoothing, e.g. lm(y~ns(x), df=_).

I want to use spline() specifically because I am using this to do the analysis represented by the plot that I am making.

Is there a simple way to use spline() in ggplot?

I have considered the hackish approach of fitting a line using

geom_smooth(aes(x=(spline(y~x)$x, y=spline(y~x)$y))

but I would prefer not to have to resort to this.

Thanks!

is this what you want?

n <- 10
d <- data.frame(x = 1:n, y = rnorm(n))
ggplot(d,aes(x,y)) + geom_point() + 
  geom_line(data=data.frame(spline(d, n=n*10)))

Alternatively, with ggformula https://rdrr.io/cran/ggformula/man/geom_spline.html, you can call ggformula::stat_spline() directly within ggplot().

library(ggplot2)
library(ggformula)

n<-1000
d <- data.frame(x = 1:n, y = rnorm(n))
ggplot(d,aes(x,y))+
  # geom_point()+
  stat_spline()

Note: OP asked specifically about using spline(). stat_spline() {ggformula} calls smooth.spline() {stats}, which might not be exactly the same implementation as spline() {stats} but think it may still be a useful answer here for others.