The nmr data and the results of each of the four smoothing methods are contained in the 
table nmrresults.s

To read these in, use the command read.table to read them into a data frame nmr.

To recapitulate the analysis presented in the paper, the following commands 
can be used:

module("wavelets")
nmr.dat <- nmr$dat
nmr.dwt_nd.dwt(nmr.dat)
nmr.expsmooth <- ebaywaveshrink(nmr.dwt)
nmr.causmooth <- ebaywaveshrink(nmr.dwt,cauchy=T)
nmr.univsmooth <- waveshrink(nmr.dwt, shrink.rule="universal")
nmr.suresmooth <- waveshrink(nmr.dwt, shrink.rule="sure")

The basic plots are produced as follow, but of course you can plot
the data in any way you wish.

plot(nmr$dat, type="l", ylim=c(-15,60), main="NMR data", ylab="signal")
plot(nmr$exp, type = "l", ylim = c(-15, 60), main = 
	"Empirical Bayes, double exponential", ylab = "signal")
plot(nmr$cau, type = "l", ylim = c(-15, 60), main = 
	"Empirical Bayes, Cauchy-tailed", ylab = "signal")
plot(nmr$sure, type = "l", ylim = c(-15, 60), main = 
		"SURE threshold", ylab = "signal")
plot(nmr$univ, type = "l", ylim = c(-15, 60), main = 
		"universal threshold", ylab = "signal")