sampling from data.frame

Hi all,
I have a data frame with "clustered" rows as follows:
Cu1  x1 y1 z1 ...
Cu1  x2 y2 z2 ...
Cu1  x3 y3 z3 ... # end of first cluster Cu1
Cu2  x4 y4 z4 ...
Cu2  x5 y5 z5
Cu2  ...               # end of second cluster Cu2
Cu3 ...
...
"cluster"-size is 3 in the example above (rows making up a cluster are
always consecutive). Is there any faster way to sample n clusters
(with replacement) from this dataframe and build up a new data frame
out of these sampled clusters? I use the "sample" function and a
for-loop.

Something like this:

cl.samps <- sample( split( df, df$cluster ), n.samps, repl=TRUE )

do.call( rbind, cl.samps )

If you need to identify the samples from which the rows came (versus just 
the originating clusters):

cl.samps2 <- lapply( seq(along=cl.samps),
 	function(x) cbind( cl.samps[[ x ]], new.cluster = x ) )

do.call( rbind, cl.samps2 )

HTH,

Chuck

Thanks in advance
Armin

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Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901