[R] running median and smoothing splines for robust surface f itting

[Liaw, Andy]

loess() should be able to do robust 2D smoothing.

There's no natural ordering in 2D, so defining running medians can be
tricky.  I seem to recall Prof. Koenker talked about some robust 2D
smoothing method at useR! 2004, but can't remember if it's available in some
packages.

Andy

From: Vladislav Petyuk
> 
> Hi,
> Are there any multidimenstional versions of runmed() and 
> smooth.spline() functions? I need to fit surface into quite 
> noisy 3D data.
> 
> Below is an example (2D) of kind of fittings I do.
> Thank you,
> Vlad
> 
> #=generating complex x,y dataset with gaussian & uniform 
> noise== x <- seq(1:10000) x2 <- rep(NA,2*length(x)) y2 <- 
> rep(NA,2*length(x)) x2[seq(1,length(x2),2)] <- x 
> x2[seq(2,length(x2),2)] <- x y2[seq(1,length(x2),2)] <- 
> sin(4*pi*x/length(x)) + rnorm(length(x)) 
> y2[seq(2,length(x2),2)] <- runif(length(x),min=-5,max=5) 
> #===============================================================
> 
> #=robust & smooth fit===========================================
> y3 <- runmed(y2,51,endrule="median") #first round of running 
> median y4 <- smooth.spline(x2,y3,df=10) #second round of 
> smoothing splines 
> #===============================================================
> 
> #=ploting data==================================================
> plot(x2,y2,pch=19,cex=0.1)
> points(x2,y3,col="red",pch=19,cex=0.1) #running median
> points(y4,col="green",pch=19,cex=0.1) #smoothing splines 
> #===============================================================
> 
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