Dear All,
I've been searching for appropriate codes to compute the rate of change and the
curvature of nonparametric regression model whish was denoted by a smooth
function but unfortunately don't manage to do it. I presume that such
characteristics from a smooth curve can be determined by the first and second
derivative operators.
The following are the example of fitting a nonparametric regression model via
smoothing spline function from the Help file in R.
#######################################################
attach(cars)
plot(speed, dist, main = "data(cars) & smoothing splines")
cars.spl <- smooth.spline(speed, dist)
lines(cars.spl, col = "blue")
lines(smooth.spline(speed, dist, df=10), lty=2, col = "red")
legend(5,120,c(paste("default [C.V.] => df =",round(cars.spl$df,1)),"s( * , df
= 10)"), col = c("blue","red"), lty = 1:2, bg='bisque')
detach()
#######################################################
Could someone please advice me the appropriate way to determine such
derivatives on the curves which were fitted by the function above and would
like to thank you in advance.
Cheers
Fir
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