From: Henrik Bengtsson <hb_at_biostat.ucsf.edu>

Date: Tue, 02 Oct 2012 17:19:38 -0700

R-devel_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-devel Received on Wed 03 Oct 2012 - 00:23:20 GMT

Date: Tue, 02 Oct 2012 17:19:38 -0700

Hi,

I'm looking for a super-duper fast mean/sum binning implementation available in R, and before implementing z = binnedMeans(x y) in native code myself, does any one know of an existing function/package for this? I'm sure it already exists. So, given data (x,y) and B bins bx[1] < bx[2] < ... < bx[B] < bx[B+1], I'd like to calculate the binned means (or sums) 'z' such that z[1] = mean(x[bx[1] <= x & x < bx[2]]), z[2] = mean(x[bx[2] <= x & x < bx[3]]), .... z[B]. Let's assume there are no missing values and 'x' and 'bx' is already ordered. The length of 'x' is in the order of 10,000-millions. The number of elements in each bin vary.

Thanks,

Henrik

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https://stat.ethz.ch/mailman/listinfo/r-devel Received on Wed 03 Oct 2012 - 00:23:20 GMT

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