I believe that smooth.spline fits a cubic B-spline to the data. So you just need to know the knot points (which are returned by smooth.spline as spl$fit$knot) and then use the bs() function in the splines library.
pinkdd wrote: > > Anybody knows how to generate the basis matrix for smoothing spline? > > And how about the smoother matrix? I tried to use the following code, but > there exist replicated data in X, and the length of smooth.spline(X, > S[,i])$y is smaller than X, and then there is error in the last step. > > spl <- smooth.spline(X, Y) > S <- diag(X) > for (i in 1:N) > S[i,] <- smooth.spline(X, S[,i])$y #smoother matrix S > > > Someone help please! Thanks in advance. > -- View this message in context: http://n4.nabble.com/Smoothing-Spline-Basis-Matrix-tp1573131p1573597.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
