R port of S Plus library haerdle

Albrecht Gebhardt   albrecht.gebhardt@uni-klu.ac.at

original README:
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`Smoothing Techniques with Implementation in S' 
by Wolfgang Haerdle, Springer, 1991

This library section contains S routines from Wolfgang Haerdle's book.
The code was typed in, but corrected with reference to code supplied by
Prof. Haerdle.  Changes made are listed in the Bugs file. No
optimizations have been made, except via the new function histog, and
to make plot.type default to true. (But see the Changes file)

Functions supplied are:

Chapter 1
histogram(data,h,x0,plot.type=T)
histog(data,h,x0,plot.type=T, ...)  -- replacement for histogram
frequency.polygon(data,h,x0)
histogram.normal.ref(data,x0,plot.type=T)
warping(x,h,M,kernel)

Chapter 2
kde(data, kernel, h, points)
uniform(x) triangle(x) epanechnikov(x) quartic(x) triweight(x) 
  gaussian(x) cosinus(x)
kds.ci(data,h,g,x,alpha)
warping.step(x,bandwidth,M,kernel)

Chapter 3
ortho.series0.1(data,N)

Chapter 4
Cv.warping(x,delta,kernel,Mstart=1,Mend)
Cvb.warping(x,delta,kernel,Mstart=1,Mend)

Chapter 5
NW.kernel(x,y, h,kernel=4, points=100,na.handling=0)
NW.Warping (x,y,h,M=10,kernel=4,na.handling=0)
k.nn(x,y,k)

Chapter 6
G.Warpingreg(x,y,delta,selector=2,kernel=4,Mstart=5,Mend,boundary=0.1)

Chapter 7
GS.Warping(x,y,h,locations,samplenumber,M=10,M.large=20,kernel=4)
twopoint.generator <- function(ndata)
Simul.conf.interval(x,y,h,alpha=0.2,N=200)
Within.group(data,beta)
Simul.conf.plot(x,y,h,alpha=0.2,N=200)

Datasets
generator(n, seed)
regression.data(n, seed)

In addition, examples.S contains source to reproduce many of the
figures and other examples.

Brian Ripley
ripley@{stats,vax}.ox.ac.uk
If in difficulty, relay via nsfnet-relay.ac.uk or prg.oxford.ac.uk
