On Fri, 16 Apr 2010, zerdna wrote:
Could someone give me an idea on how to do rolling ranking, i.e. rank in the
moving window of last 100 numbers in a long vector? I tried naive solution
like
roll.rank<-function(v, len){
r<-numeric(length(v)-len+1)
for(i in len:length(v))
r[i-len+1]<-rank(v[(i-len+1):i])[len]
r
}
However, it turns out pretty slow even on my rather able Linux box. For
example, doing roll.rank(rnorm(50000), 100) takes 5 second, so for typical
data i operate which is matrices of the size 1000 x 50000 i will need to
wait 1.5 hours for one calculation. Does someone know a trick to properly do
it quicker?
Vectorize it with embed:
x <- rnorm(50000)
system.time(x.rank <- rowSums(x[ -(1:99) ] >= embed(x,100) ))
user system elapsed
0.295 0.131 0.424
system.time(x.rank.2 <- roll.rank(x,100))
user system elapsed
6.907 0.033 6.940
all.equal(x.rank,x.rank.2)
[1] TRUE
N.B., if there are ties, you may want to adjust when
rowSums(x[ -(1:99) ] == embed(x,100) )
is greater than 1.
If you want much faster, package inline would enable you to write
something equivalent in C.
HTH,
Chuck
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Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
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