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...the value that way - by focusing on the best matches. If there are any other thoughts on how to do this (relatively easily), I'm open to suggestions and being educated. Thanks, Danny > From: Art Kendall <Art at DrKendall.org> > Date: 2004/02/13 Fri PM 02:47:00 EST > To: Danny Heuman <a0079454 at airnews.net> > Subject: Re: Find Closest 5 Cases? > > This would be extremely compute intensive. > Why are you trying to do this? > Do the 5 percentages sum to a constant total? > > If you tell us more about the problem and its context perhaps we can make s...

I have data in i,j,r format, where r is the value in location A[i,j] for some imaginary matrix A. I need to build this matrix A, but given the sizes of i and j, I believe that using a sparse format would be most adequate. Hopefully this will allow me to perform some basic matrix manipulation such as multiplication, addition, rowsums, transpositions, subsetting etc etc. Is there any way

Hi all, I've got some functioning code that I've literally taken hours to write. My 'R' coding is getting better...it used to take days :) I know I've done a poor job of optimizing the code. In addition, I'm missing an important step and don't know where to put it. So, three questions: 1) I'd like the resulting output to be sorted on distance (ascending) and

Hi all, Is it possible to run kmeans, pam or clara with a constraint such that no resulting cluster has fewer than X cases? These kmeans algorithms often find clusters that are too small for my use. There are usually a few clusters with 1-10 cases (generally substantial outliers). I then have to manually assign the small ones to other sizable clusters. If this doesn't exist, it there such

Hi all, I've got clusters and would like to match individual records to each cluster based on a sum of squares deviation. For each cluster and individual, I've got 50 variables to use (measured in the same way). Matrix 1 is individuals and is 25000x50. Matrix 2 is the cluster centroids and is 100x50. The same variables are found in each matrix in the same order. I'd like to

I appreciate the help I've been given so far. The issue I face is that the data I'm working with has 53000 rows, so in calculating distance, finding all recids that fall within 2km and summing the population, etc. - a) takes too long and b) have no sense of progress. Below is a loop that reads each recid one at a time, calculates the distance and identifies the recids that fall within 2