<posted & mailed> Dear all,
I'm trying to solve the problem, of how to find clusters of values in a vector that are closer than a given value. Illustrated this might look as follows: vector <- c(0,0.45,1,2,3,3.25,3.33,3.75,4.1,5,6,6.45,7,7.1,8) When using '0.5' as the proximity requirement, the following groups would result: 0,0.45 3,3.25,3.33,3.75,4.1 6,6.45 7,7.1 Jim Holtman proposed a very elegant solution in http://tolstoy.newcastle.edu.au/R/e2/help/07/07/21286.html, which I have modified and perused since he wrote it to me. The beauty of this approach is that it will not only work for constant proximity requirements as above, but also for overlap-windows defined in terms of ppm around each value. Now I have an additional need and have found no way (short of iteratively step through all the groups returned) to figure out how to do that with Jim's approach: how to figure out that 6,6.45 and 7,7.1 are separate clusters? Thanks for any hints, Joh ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
